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Analysis of zoochemical from Meretrix casta (Mollusca: Bivalvia) extracts, collected from Rameswaram, Tamil Nadu, India and their pharmaceutical activities
The marine ecosystem's diverse animal species offer a unique opportunity to discover marine-derived natural products. While numerous invertebrates have been studied, research on Indian marine invertebrates, especially Meretrix casta, remains limited. This study explores the zoochemical composition of ethyl acetate and methanolic extracts from Meretrix casta off Rameswaram, Tamil Nadu, India, and evaluates their bioactive potential, focusing on antioxidant properties, glucose uptake in yeast cells, and alpha-amylase activity. The results reveal the presence of alkaloids, flavonoids, polyphenols, sterols, terpenoids, and cardiac glycosides in both extracts, highlighting their bioactive potential. Although their antioxidant capacity is slightly lower than ascorbic acid, the extracts demonstrated significant alpha-amylase inhibition, suggesting their potential in blood sugar regulation and diabetes management. These findings underscore the therapeutic potential of M. casta in developing anti-diabetic compounds, warranting further pharmacological exploration. Authors. -
Analysis of Workloads for Cloud Services
Capturing best quality datasets for a study is the first evidence for better outcomes of research. If the analysis are based on such datasets, then the metrics, the characteristics and few factors determines proof point for well proven theories. Hence it is obvious that we rely on the best possible ways to arrive at such data acquiring sources. It can be either based on historical techniques or from the innovations in application of it to industry. This paper introduces a mapping framework for analyzing, and characterizing data previously used by research community and how they are made to fit for Cloud systems, i.e. using 'workloads' and 'datasets' as the 'refined definitions'. It was contributed in the past two decades within the scientific community setting their own workflow analysis mechanisms. The framework thus is validated by acquiring a sample workload per layer of cloud. The sources are form the literature that are available from existing scientific theories. These workloads are then experimented against the three tiers of the cloud computing ie., IaaS(Infrastructure as a Service), PaaS(Platform as a Service), & SaaS(Software as a Service). The selected data is analyzed by the authors for an offline model presented here based on the Machine Learning tool-kits. There are future studies planned for and to be experimented in a cloud auto scaled environment with online model as well. 2022 IEEE. -
Analysis of Web Mining Patterns Using Custom-Built Apriori Algorithm
The dissertation entitled Analysis of Web Mining Patterns Using Custom-Built Apriori Algorithm has developed a custom-built apriori algorithm for the discovery of association rules in web log data. Web server log containing the information about all the web requests to the Christ university website is used for analysis. The methodology adapted by this research is a four step process, containing data preprocessing, frequent pattern discovery, analysis and developing a tool for implementing web mining. The custom built apriori takes the preprocessed weblog file as input and generates the frequent folders and the relationship among them. This thesis has also developed a tool written in java for this web usage mining process. The tool assists the user to execute the custom built apriori algorithm and to view the associations among folders based on the given support and confidence values to the tool. The web is a highly dynamic information source. Most of the organisations put information on the web because they want it to be seen by the world. Now a days the web is well beefed up with more information in an unstructured fashion. As the web and its usage continue to grow, there is an opportunity to analyse web data and extract useful knowledge from it. The objective of this research is to predict the user behaviour in interacting with the website that helps the website designer in improving the quality of website. The dissertation is organised into 5 chapters. Chapter1, Introduction starts with a brief overview of web mining and presents the objective of the study and the problem statement. Chapter 2, Literature review, discusses background work in the field of web mining and pattern discovery. Chapter 3, methodology elaborately discusses the process used for analysing the web patterns. Chapter 4 is dedicated for results and discussion. Chapter5, conclusion, summarises the inferences concluded based on the results obtained. The chapter also discusses the limitations and challenges and concludes with future scope of the study. KeyWords: Web Mining, Preprocessing, Web Server log, Frequent pattern -
Analysis of Web Mining Patterns Using Custom-Built Apriori Algorithm
The dissertation entitled Analysis of Web Mining Patterns Using Custom-Built Apriori Algorithm has developed a custom-built apriori algorithm for the discovery of association rules in web log data. Web server log containing the information about all the web requests to the Christ university website is used for analysis. The methodology adapted by this research is a four step process, containing data preprocessing, frequent pattern discovery, analysis and developing a tool for implementing web mining. The custom built apriori takes the preprocessed weblog file as input and generates the frequent folders and the relationship among them. This thesis has also developed a tool written in java for this web usage mining process. The tool assists the user to execute the custom built apriori algorithm and to view the associations among folders based on the given support and confidence values to the tool. The web is a highly dynamic information source. Most of the organisations put information on the web because they want it to be seen by the world. Now a days the web is well beefed up with more information in an unstructured fashion. As the web and its usage continue to grow, there is an opportunity to analyse web data and extract useful knowledge from it. The objective of this research is to predict the user behaviour in interacting with the website that helps the website designer in improving the quality of website. The dissertation is organised into 5 chapters. Chapter1, Introduction starts with a brief overview of web mining and presents the objective of the study and the problem statement. Chapter 2, Literature review, discusses background work in the field of web mining and pattern discovery. Chapter 3, methodology elaborately discusses the process used for analysing the web patterns. Chapter 4 is dedicated for results and discussion. Chapter5, conclusion, summarises the inferences concluded based on the results obtained. The chapter also discusses the limitations and challenges and concludes with future scope of the study. KeyWords: Web Mining, Preprocessing, Web Server log, Frequent pattern -
Analysis of value and growth styles of investing : A study on nifty 100 index stocks of NSE /
Asian Journal Of Research In Business Economics And Management, Vol.7, Issue 5, pp.165-177, ISSN: 2249-7307. -
Analysis of unsteady flow of blood conveying iron oxide nanoparticles on melting surface due to free convection using Casson model
Iron oxide nanoparticles have great importance in future biomedical applications because of their intrinsic properties, such as low toxicity, colloidal stability, and surface engineering capability. So, blood containing iron oxide nanoparticles are used in biomedical sciences as contrast agents following intravenous administration. The current problem deals with an analysis of the melting heat transfer of blood consisting iron nanoparticles in the existence of free convection. The principal equations of the problem are extremely nonlinear partial differential equations which transmute into a set of nonlinear ordinary differential equations by applying proper similarity transformations. The acquired similarity equalities are then solved numerically by Runge-Kutta Felhsberg 45th-order method. The results acquired are on the same level with past available results. Some noteworthy findings of the study are: the rate of heat transfer increases as the Casson parameter increases and also found that the temperature of the blood can be controlled by increasing or decreasing the Prandtl number. Hence, we conclude that flow and heat transfer of blood have significant clinical importance during the stages where the blood flow needs to be checked (surgery) and the heat transfer rate must be controlled (therapy). 2020 Wiley Periodicals LLC -
Analysis of Unintelligible Speech for MLLR and MAP-Based Speaker Adaptation
Speech Recognition is the process of translating human voice into textual form, which in turn drives many applications including HCI (Human Computer Interaction). A recognizer uses the acoustic model to define rules for mapping sound signals to phonemes. This article brings out a combined method of applying Maximum Likelihood Linear Regression (MLLR) and Maximum A Posteriori (MAP) techniques to the acoustic model of a generic speech recognizer, so that it can accept data of people with speech impairments and transcribe the same. In the first phase, MLLR technique was applied to alter the acoustic model of a generic speech recognizer, with the feature vectors generated from the training data set. In the second phase, parameters of the updated model were used as informative priors to MAP adaptation. This combined algorithm produced better results than a Speaker Independent (SI) recognizer and was less effortful for training compared to a Speaker Dependent (SD) recognizer. Testing of the system was conducted with the UA-Speech Database and the combined algorithm produced improvements in recognition accuracy from 43% to 90% for medium to highly impaired speakers revealing its applicability for speakers with higher degrees of speech disorders. 2021, Springer Nature Singapore Pte Ltd. -
Analysis of U-Net and Modified VGG16 Technique for Mitosis Identification in Histopathology Images
One of the most frequently diagnosed cancers in women is breast cancer. Mitotic cells in breast histopathological images are a very important biomarker to diagnose breast cancer. Mitotic scores help medical professionals to grade breast cancer appropriately. The procedure of identifying mitotic cells is quite time-consuming. To speed up and improve the process, automated deep learning methods can be used. The suggested study aims to conduct analysis on the detection of mitotic cells using U-Net and modified VGG16 technique. In this study, pre-processing of the input images is done using stain normalization and enhancement processes. A modified VGG16 classifier is used to classify the segmented results after the altered image has been segmented using U-Net technology. The suggested method's robustness is evaluated using data from the MITOSIS 2012 dataset. The proposed strategy performed better with a precision of 86%,recall of 75% and F1-Score of 80%. 2024 IEEE. -
ANALYSIS OF TRANSITION OF FOLKTALE FROM ORAL TO TEXT TO VISUAL MEDIA CASE STUDY: KEIBU KEIOIBA (MANIPURI FOLKTALE)
Folklore is an art form, which consists of stories, songs, spells, proverbs, legends, belief, and other principles in a tradition of a culture, subculture, etc. The term "folk" can refer to any group of people whatsoever who share at least one common factor. In Manipuri tradition, the elders or grandparents to their grandchildren near a place called ??Phunga which means a ??fireplace in the vicinity of kitchen narrate folktale orally. It is a place where members of the family dines together and shares the stories of daily life. Hence, the name ??Phunga wari which means ??fireplace tale is also known as ??folktale in Manipuri culture. Manipur has a rich tradition of folktales since its inception. Keibu Keioiba is one of the most widespread folktales in Manipur. It is translated in many ways such as tiger head, half beast half human and a man tiger. It is represented in different ways: written (books), oral (oral transmission) and visual media (animation movie). The study aims to analyse the folktale Keibu Keioiba from oral tradition; books and animated movie to study the characteristics changes in the transition of medium. -
Analysis of the Viscous Dissipation and Nonlinear Velocity Slip Effect on the Thin Film Nanofluid Flow
Abstract: In the contemporary study, the dynamics of the nanofluid thin film is investigated by considering the viscous dissipation and chemical reaction effects. Additionally, the surface is assumed to have a nonlinear slip rather than the conventional no-slip conditions. This helps in better flow and heat transfer characteristics. This nonlinear velocity slip at the boundary is modelled using the idea proposed by Thompson and Troian. Also, the presence of viscous dissipation in the energy equation, depicts the loss of energy due to the internal friction. Hence, the viscous dissipation turns out to be a critical factor in determining the thermal properties of the nanofluid thin film. The chemical reactions take place within the system because of the presence of nanoparticles, that in turn will have a significant impact on the mass transfer characteristics of the thin film nanofluid. The incorporation of the similarity transformation helps in converting the partial differential equations (PDEs) that govern the fluid flow into a system of nonlinear ordinary differential equations (ODEs). This resulting system is then solved using the BVP package in python whose accuracy is assessed through residual analysis. By this error analysis, convergence of residues was confirmed. Thus validating the method and the results obtained. The outcomes of the study are interpreted through the graphs which highlighted the intensification of heat transfer for the increase in the Eckert number while the magnetic field confirmed its flow controlling feature. Also, the streamlines and contours were plotted to understand and visulaise the flow, all these contours showed the significance of the presence of nonlinear velocity slip at the boundary. Pleiades Publishing, Ltd. 2025. -
Analysis of the UAV Flight Logs in Order to Identify Information Security Incidents
The article discusses issues related to the analysis of the UAV flight logs to identify information security incidents that occurred during flights. Existing methods and tools for analyzing logs are described, and sources for obtaining logs are presented. In the main part of the article, first, the parameters important for the analysis are highlighted. The features of analyzing the values in the flight logs for the detection of two types of attacksGPS Spoofing and GPS Jamming are also given. For this purpose, the parameters that are most important for the detection of each of these attacks have been identified, systems of equations have been compiled to analyze these parameters, the calculations of which make it possible to detect the fact of attacks with high efficiency. The paper also presents the developed software that implements a number of functions that allow automating the analysis of flight logs, as well as determining the presence of information security incidents that occurred during the flight. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Analysis of the Thomson and Troian velocity slip for the flow of ternary nanofluid past a stretching sheet
In this article, the flow of ternary nanofluid is analysed past a stretching sheet subjected to Thomson and Troian slip condition along with the temperature jump. The ternary nanofluid is formed by suspending three different types of nanoparticles namely TiO 2, Cu and Ag into water which acts as a base fluid and leads to the motion of nanoparticles. The high thermal conductivity and chemical stability of silver was the main cause for its suspension as the third nanoparticle into the hybrid nanofluid Cu-TiO 2/ H 2O. Thus, forming the ternary nanofluid Ag-Cu-TiO 2/ H 2O. The sheet is assumed to be vertically stretching where the gravitational force will have its impact in the form of free convection. Furthermore, the presence of radiation and heat source/sink is assumed so that the energy equation thus formed will be similar to most of the real life applications. The assumption mentioned here leads to the mathematical model framed using partial differential equations (PDE) which are further transformed to ordinary differential equations (ODE) using suitable similarity transformations. Thus, obtained system of equations is solved by incorporating the RKF-45 numerical technique. The results indicated that the increase in the suspension of silver nanoparticles enhanced the temperature and due to density, the velocity of the flow is reduced. The slip in the velocity decreased the flow speed while the temperature of the nanofluid was observed to be increasing. 2023, The Author(s). -
Analysis of the spread of infectious diseases with the effects of consciousness programs by media using three fractional operators
In this chapter, the mathematical model spread of infectious diseases exemplifying the effects of awareness programs by media is studied with the help of newly proposed fractional operators. The solution for the system of equations exemplifying the model is obtained with the help of the q-homotopy analysis transform technique (q-HATT). The projected method is an elegant amalgamation of the q-homotopy analysis scheme and the Laplace transform. Three fractional operators are employed in this study to show their essence in generalizing the models associated with power-law distribution: kernel singular, nonlocal, and nonsingular. The fixed-point theorem employed to present the existence and uniqueness for the hired arbitrary-order model and converges for the solution is derived with Banach space. The projected scheme springs the series solution rapidly convergent, and it can guarantee the convergence associated with the homotopy parameter. Moreover, for diverse fractional-order, the physical nature has been captured in plots. 2022 Elsevier Inc. All rights reserved. -
Analysis of the pooled effect of compression ratio and injection timing variation on conventional diesel engine powered with nano doped biodiesel blend
This research aims to explore how incorporating nanoparticles into a biodiesel-diesel blend influences the performance, combustion, and emission characteristics of a diesel engine under varying conditions, including compression ratios, engine loads, and injection timings. The biodiesel and nanoparticles considered for this investigation are mahua biodiesel and Titanium oxide nanoparticles (TiO2), respectively. The experimental fuel is formulated by blending diesel and mahua biodiesel with the addition of titanium oxide nanoparticles. In this study, compression ratio is varied from 17.5 to 18, whereas fuel injection timing of 20, 23, and 25 BTDCs along with engine load variation of 20%, 40%, 60%, 80%, and 100% are considered. The experimentation utilized a single-cylinder diesel engine equipped with a variable compression ratio (VCR) feature and a power output of 3.5kW. The results indicate that the maximum brake thermal efficiency was achieved at a compression ratio of 18 and a fuel injection timing of 20 before Top Dead Center. For the same setting, the nanoparticle-enriched biodiesel-diesel blend exhibited the lowest levels of CO and HC emissions among all test runs, with reductions of 45.34% and 40%, respectively, compared to standard diesel operation. The Author(s) 2025. -
Analysis of the photo-thermal excitation in a semiconducting medium under the purview of DPL theory involving non-local effect
Non-local theory comprises a unique characteristics by analyzing the effects of all points of the body on a single point of the material. The present study enlightens the propagation of photo-thermal waves in a semiconductor by adopting the two phase lag theory of thermoelasticity in the frame of non-local effect. Normal mode analysis has been employed to obtain the exact expressions of the field quantities such as temperature, components of the displacement, carrier density, and components of the stress. Each field quantity is found to be influenced by the non-local parameter as well as phase lags. Quantitative results are determined in the time-domain by adopting a suitable technique of Laplace transform inversion which exhibit the influence of the non-locality effect on the distributions of field variables. Significant differences have been attributable to the studied fields due to the non-locality effect. Also, computational results are compared with the corresponding results obtained by using single phase lag theory proposed by Lord and Shulman (LS model)LS model single phase lag model (LS model). 2022, Springer Nature B.V. -
Analysis of the Performance of VAR Models as a tool for Market Risk
The International Journals Research Journal of Social Science & Management Vol.2, No.10 pp.74-83. ISSN No. 2251-1571 -
Analysis of the Performance of a 5-Level Modular Multilevel Inverter for a Solar Grid-Connected System
The main purpose of a multilevel inverter is to combine numerous levels of DC voltage to create a nearly sinusoidal voltage. The synthesized output waveform has more stages as the number of levels rises, creating a staircase ripple which resembles the preferred waveform. As the number of voltage levels rises, the output waves harmonic distortion diminishes and eventually approaches zero. In particular, the performance analysis of a five-level inverter with variable loads is highlighted in this paper. This topology has fewer devices than traditional multilevel inverters for the same five output levels, which makes it more affordable due to lesser driver circuits. The proposed modular five level topology is simulated using both high frequencies switching pulse width modulation and basic frequency switching modulation techniques. The output voltage, current waveform, and total harmonic distortion are examined and compared using simulink to confirm the viability of the modular multilevel inverter topology. 2024, TUBITAK. All rights reserved. -
Analysis of the Effectiveness of a Two-Stage Three-Phase Grid-Connected Inverter for Photovoltaic Applications
This paper proposes a two-stage three-phase grid-connected inverter for photovoltaic applications. The proposed inverter topology consists of a DC-DC boost converter and a three-phase grid-connected inverter. The DC-DC boost converter is used to boost the low voltage DC output of the PV array to a high voltage DC level that is suitable for feeding into the grid-connected inverter. The three-phase grid-connected inverter is used to convert the high voltage DC output of the boost converter into a three-phase AC output that is synchronized with the grid voltage. The proposed inverter topology offers several advantages over traditional single-stage inverters. Firstly, the DC-DC boost converter allows for the use of a smaller, more efficient inverter in the second stage, reducing the overall cost of the system. Secondly, the use of a boost converter allows for the maximum power point tracking of the PV array, which can increase the overall efficiency of the system. The proposed inverter topology offers improved control of the grid current, reducing the impact of the PV system on the grid. The proposed topology has been simulated using MATLAB/Simulink and the results show that the system is capable of delivering a high-quality three-phase AC output with low harmonic distortion. The Author(s). Publisher: University of Tehran Press. -
Analysis of the chemical properties and high-temperature rheological properties of MDI modified bio-asphalt
As an environmentally friendly material, bio-oil is employed to partially replace non-renewable petroleum asphalt, but its addition weakens the high-temperature non-deformability of petroleum asphalt. Therefore, the 4,4?-diphenylmethane diisocyanate (MDI) was employed as a chemical modifier of bio-asphalt to improve its high temperature rheological properties. The MDI with addition of 0.5%, 1%, 2%, 4% by weight, and the bio-oil with addition of 12% were used to obtain the MDI modified bio-asphalts. The chemical reaction mechanism between the MDI and bio-asphalt was analyzed by employing the Fourier-transform infrared spectroscopy (FTIR) and gel permeation chromatography (GPC) tests. Meanwhile, the rotational plate viscosity (RPV) test, the temperature sweep test, and the multiple stress creep and recovery (MSCR) test were employed to evaluate the high-temperature rheological properties of the MDI modified bio-asphalts. Moreover, the relationships between the chemical reaction mechanism and high-temperature rheological parameters of MDI modified bio-asphalt were established. Test results show that a nucleophilic addition reaction occurred between the MDI and the active hydrogen of bio-asphalt to form urethane chains, which increased the content of macromolecular polymers in the bio-asphalt. The MDI increased the G*/sin? (rutting factor) and the E(?) (visco-flow activation energy) of the bio-asphalt, but decreased its permanent strain and Jnr (non-recoverable creep compliance). Therefore, the MDI modifier effectively enhanced the permanent non-deformability of the bio-asphalt. Both IUrethane and LMS were positively correlated with the rutting factor, viscosity and 1/Jnr, and had significant correlations at a significance level of 0.05. Furthermore, the optimal ratio of MDI to bio-oil was determined to be 1:6 by mass. 2020 Elsevier Ltd -
Analysis of Systematic Trade-offs between Military and Healthcare Expenditure alongside GDP Growth of Select Asian and Western Exporting Economies in the 21st Century
This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality between GDP growth and healthcare expenditure, reflecting economic stability and balanced allocation patterns. In contrast, developing Asian nations display fragmented and volatile relationships due to resource constraints and inefficiencies. Outlier analysis reveals country-specific dynamics, such as conflict-driven spending in Afghanistan and Myanmar and growth-focused strategies in China. Temporal trends show that economic crises, like the COVID-19 pandemic, significantly disrupt GDP growth but have limited long-term effects on healthcare or military expenditures. Clustering analysis identifies distinct groups of nations, shaped by economic capacity and geopolitical pressures. The findings emphasize the need for tailored policy frameworks to balance national security and human well-being, particularly in developing nations facing structural challenges. For sustainable development, policies must align resource allocation with economic priorities, geopolitical contexts, and societal needs. 2025, Binghamton University Libraries. All rights reserved.