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Static perfect fluid space-Time and paracontact metric geometry
The main purpose of this paper is to study and explore some characteristics of static perfect fluid space-Time on paracontact metric manifolds. First, we show that if a K-paracontact manifold M2n+1 is the spatial factor of a static perfect fluid space-Time, then M2n+1 is of constant scalar curvature-2n(2n + 1) and squared norm of the Ricci operator is given by 4n2(2n + 1). Next, we prove that if a (?,?)-paracontact metric manifold M2n+1 with ? >-1 is a spatial factor of static perfect space-Time, then for n = 1, M2n+1 is flat, and for n > 1, M2n+1 is locally isometric to the product of a flat (n + 1)-dimensional manifold and an n-dimensional manifold of constant negative curvature-4. Further, we prove that if a paracontact metric 3-manifold M3 with Q? = ?Q is a spatial factor of static perfect space-Time, then M3 is an Einstein manifold. Finally, a suitable example has been constructed to show the existence of static perfect fluid space-Time on paracontact metric manifold. 2022 World Scientific Publishing Company. -
STATIC PERFECT FLUID SPACE-TIME ON ALMOST KENMOTSU MANIFOLDS
In this work, we intend to investigate the characteristics of static perfect fluid space-time metrics on almost Kenmotsu manifolds. At first we prove that if a Kenmotsu manifold M is the spatial factor of static perfect fluid space-time then it is ?-Einstein. Moreover, if the Reeb vector field ? leaves the scalar curvature invariant, then M is Einstein. Next we consider static perfect fluid space-time on almost Kenmotsu (?, ?)0-manifolds and give some characteristics under certain conditions. 2021 Bulgarian Academy of Sciences. All rights reserved. -
Static voltage stability of reconfigurable radial distribution system considering voltage dependent load models
This paper presents the static voltage stability analysis of RDS. Initially the performance of RDS is evaluated using backward/forward load flow considering voltage-dependent load modeling. Later, the load flow solution is used for determining the static voltage stability of the system. The analysis is performed for different type of loads such as constant power, constant current, constant impedance, residential, industrial, commercial, agricultural and electric vehicle loads. The simulations are performed for standard and optimal reconfigured topology of standard IEEE 33-bus test system. The comparative study reveals the importance of load type and topology while assessing the static stability analysis of radial distribution systems. 2020, International Information and Engineering Technology Association. -
Statistic analysis of IPL match score and winner inning wise using machine learning algorithms
This study explains the statistical analysis of cricket match score prediction using machine learning. According to recent changes in data science and sports, the use of sports-based machine learning and data mining shows the importance of process in outcome performance and prediction. The scope of this research paper is to evaluate current measurements used in the previous work to understand the estimation the ways used to model and analyze data and characterize the variables that govern performance using statistical methods. Actually, this research article will present a reliable statistical tool for data analysis using machine learning algorithms. At present, sports organizations produce enough statistical information on every player, team, match, and season for particular related sports. The first sports researchers were thought to be experts, coaches, team managers, and analysts. Sports organizations want to do statistical analysis of player from their previous data stored on their database using different data mining and machine learning algorithms. Sports data helps coaches and managers in many ways, such as predicting results, analyzing player performance, and skills, and evaluating strategies. Forecasts help managers and organizations make decisions to win teams and competitions. The current evaluation of research shows that primary studies of data mining systems can predict outcomes and evaluate the strengths and weaknesses of each system. Statistical analyses are made for each match for result predictions. Although in many respects this application is very limited. These are prime factors which important to examine machine learning algorithms in these situations to see if the application can give the nearest results in analysis. This research aims to give solutions that will help to make predictions more accurate and precise than previous methods, using more accurate data and machine learning. 2024, Taru Publications. All rights reserved. -
Statistical Analysis of Ecological Mathematical Model Based on Data Warehouse
Persistence of ecosystems, existence and stability of periodic and almost periodic solutions, and global attractiveness are important research contents in ecological mathematical theory. This article takes the ocean as an example to illustrate. The marine ecological model management system integrates marine technology, Internet technology and database technology. The purpose is to collect, organize and analyze mathematical models related to marine ecosystems, integrate them according to certain classification principles, and store them in the form of text. In the database, the query of the database according to the important parameters in the mathematical model or the classification of the mathematical model is provided on the Internet, and the queried mathematical model is displayed on the screen through the browser. This paper adopts the method of data warehouse. How to effectively use resources is an important aspect of whether to take the initiative in competition. Data warehouse can play the characteristics of information processing and has broad application prospects in the face of competition in the field of telecommunications. 2023 IEEE. -
Statistical analysis of stagnation-point heat flow in Williamson fluid with viscous dissipation and exponential heat source effects
This analysis explores the effect of the novel exponential space-dependent heat generation factor on the stagnation-point Williamson fluid flow over a stretchable surface. The heat transport phenomenon is carried out by the addition of viscous and Ohmic dissipations. Similarity transformations are applied to the nonlinear system of partial differential expressions that arise by the flow. The nonlinear ordinary differential system hence obtained is solved to visualize the role of different constraints graphically. Statistical methods such as correlation, probable error, and regression are utilized. The probable error is evaluated to calculate the reliability of the computed correlation factors. The study reveals that the velocity phenomenon is reduced by incrementing the Weissenberg parameter. The velocity of the hydromagnetic liquid is lesser than the velocity of magnetohydrodynamic fluid flow. Also, the higher heat generation factor gives a boost to the temperature of the flowing material. 2020 Wiley Periodicals LLC -
Statistical and experimental studies of MoS2/g-C3N4/TiO2: a ternary Z-scheme hybrid composite
Abstract: A ternary photocatalyst, MoS2/g-C3N4/TiO2, was prepared using layered and exfoliated MoS2, g-C3N4, and TiO2 viahydrothermal and wet chemical method. It was characterized using various methods to evaluate the structural, morphological and optical properties. Successful incorporation of g-C3N4 and TiO2into MoS2 was confirmed by X-ray photoelectron spectroscopy, and the formation of heterojunctions among MoS2, g-C3N4 and TiO2 particles was established by transmission electron microscopy. These hybrid composites exhibited excellent efficiency in the degradation of malachite green dye. The composite can be recycled four times without loss of photoactivity. The remarkable improvement in photocatalytic efficiency was because of the synergism among the three nanoparticlesthrough the Z-scheme pathway which allows separation of electronhole pairs and makes MoS2/g-C3N4/TiO2 an outstanding material in the fields of photocatalysis and water treatment. The optimized experimental conditions for the degradation of the dye were assessed by the BoxBehnken design of the response surface methodology. Graphical abstract: [Figure not available: see fulltext.]. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Statistical Data Analysis of Anticorrosion and Antifouling: Unveiling Insights from Performance and Trends
This chapter provides intended insights about the current antifouling and anticorrosion conventional coatings, each with a distinct quality, that fall short of fully satisfying the contemporary requirements of material preservation in a marine environment. To solve these issues and accomplish the required goals, a number of novel terminologies and procedures have been investigated and several recently published research works were referred to and briefly examined in order to provide appropriate conclusions. In order to explore new methodologies that provide total protection for materials from biofouling and corrosion in maritime environments, this study looks into the complex realm of antifouling and anticorrosion methods. 2024 Scrivener Publishing LLC. -
Statistical features from frame aggregation and differences for human gait recognition
Human gait recognition, an alternate biometric technique, received significant attention in the last decade. As many gait recognition applications require real-time response, the primary concern is to design efficient and straightforward gait features for human recognition. In this work, two novel gait features are proposed. Both features are designed by exploring the dynamic variations of different body parts during a gait cycle. The first feature set is based on one-against-all gait frame differences for person identification. This novel approach divides each frame in a gait cycle to blocks, compute the block sum, and then find the difference of respective block sum between the first frame and the rest. The second feature set is defined on the first-order statistics of the normalized sum of the frames in a cycle. Two other existing features- Centroid of Silhouette frames and feature values defined on Change Energy Images are also considered. Feature level fusion is realized by considering the different combinations of the four types of features. Experiments carried out with the CASIA Gait Dataset B demonstrated the proposals merit with high recognition accuracy. The outcome of the investigations is promising when compared to recent contributions. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature. -
Statistical features learning to predict the crop yield in regional areas
The plethora of information presented in the form of benchmark dataset plays a significant role in analyzing and understanding the crop yield in certain regions of regional territory. The information may be presented in the form of attributes makes a prediction of crop yield in various regions of machine learning. The information considered for processing involves data cleaning initially followed by binning to reduce the missing data. The information collected is subjected to clustering of data items based on patterns of similarity, The data items that are similar in nature is fed to the system with similarity measure, which involves understanding the distance of data items from its related data item leading to hyper parameters for analyzing of information while calculating the crop yield. The information may be used to ascertain the patterns of data that exhibit similarity with nearest neighbor represented by another attribute. Thus, the research method has yielded an accuracy of 89.62% of classification for predicting the crop yield in agricultural areas of Karnataka region. 2022 Institute of Advanced Engineering and Science. All rights reserved. -
Statistical Forecasting of Fat in Body Proportion Utilizing Nonlinear Anthropological Parameters and Density Evaluation
Body Fat Percentage (BFP) is an accurate body fat assessment, plays vital role in order to evaluate an individual's health status and disease risk. Traditional BFP assessments, such as dual-energy X-ray absorptiometry (DXA) and hydrostatic weighing are high in accuracy which is compromised by their cost and complexity. This research work focuses on creating a predictive BFP model using anthropometric techniques. For formulating and validating the proposed model, a benchmark dataset is used consisting of 252 samples having measures of weight, height, waist circumference (WC), hip circumference (HC), skinfold thicknesses along with air displacement plethysmography (ADP) based density estimates. For feature engineering, the most important values are selected such as body mass index, hip ratio etc., as well as logarithmic values and then the best artificial neural network model is trained. The proposed model is developed using quadratic polynomial terms with a literature-based space-cost function (r > 0.98), provided the best model with a Mean Absolute Error (MAE) of 1.5% and coefficient of determination R = 0.92 outperforming conventional works. 2025 IEEE. -
Statistical Learning inPharmacovigilance: A Data-Driven Approach to AI-Enhanced Drug Safety Monitoring
Pharmacovigilance is transforming at warp speed in response to big data and advanced analytical techniques. This paper will provide an overview of where pharmacovigilance currently stands by focusing on integrating artificial intelligence (AI), machine learning (ML) and real-world data (RWD) in order to improve drug safety monitoring. These new methods are increasingly supplementing traditional ones which serve as their base. The purpose of this survey is to assess how effective they are, point out the major challenges standing in their way as well as offer recommendations for future research. In conclusion, although AI and ML could prove helpful especially with handling large volume and complexity of datasets, there is a need for tackling data quality, integration issues and regulatory acceptance concerns first. Standardized methodologies should be worked out and collaboration among all stakeholders encouraged so as to maximize the pharmacovigilance benefits that can come from these technologies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Statistical modelling of software source code
This book will focus on utilizing statistical modelling of the software source code, in order to resolve issues associated with the software development processes. Writing and maintaining software source code is a costly business; software developers need to constantly rely on large existing code bases. Statistical modelling identifies the patterns in software artifacts and utilize them for predicting the possible issues. Statistic tool for the software engineer. 2021 Walter de Gruyter GmbH, Berlin/Boston. -
Statistical tests for key strength identification in cryptography
The cryptographic study involves three algorithms, one for Encryption of Plain text to Cipher text, one for Decryption for Cipher text back to Plain text and third for the generation of the Key. Key generation algorithm works on the principle of Randomness. In this work, the randomness of Key is studied by using Statistical methods like Runs Up & Runs Down test, Runs (Above and Below the mean), Chi Square test & Auto correlation test for its usability in Cryptographic study. 2020 IJSTR. -
Statistical thermal study of ternary hybrid nanofluid flow in coaxial cylinder: artificial neural network approach
The objective of this study is to examine heat and mass transfer aspects of ternary nanofluid flow in coaxial cylinder under the influence of Arrhenius activation energy, microorganisms concentration and bioconvection Peclet number, which a pivotal rolet in various scientific and engineering applications. The flow of ternary nanofluid is caused due to stretching inner cylinder with stationary outer cylinder. The nonlinear partial equations are derived for the flow model and reduced to non-linear ordinary differential equation by applying suitable similarity transformation. The resultant equations are resolved mathematically using Runge Kutta Fehlberg (RKF45) technique. The obtained numerical results are validated with the published work to check the exactness of the solution methodology and it is noticed that the present outcomes are on par with published work. The physical behaviour of the pertinent parameters is analysed through graphical depiction. The derived quantities like drag force and Sherwood number are studied through tabular column. Additionally, the heat transfer rate is analysed by using backpropagated Levenberg-Marquardt Machine learning algorithm. Further, the correlation between the parameter on the rate of heat transfer is analysed by using Mean square error and regression graphs. The key outcome of this research is that, the temperature upsurges by increasing the solid volume of nanoparticle due to higher thermal conductivity of the nanoparticles. Further, it is perceived from the artificial neural network model that, the correlation between the input parameters and output data are strongly correlated (R = 1). 2025 -
Steady Finite Amplitude Convection in Type 2 Hybrid Nanofluids with Rough Boundaries and Robin Boundary Condition on Temperature
The study concerns linear and weakly non-linear analysis of a Rayleigh-Bard convection problem subjected to a most general boundary condition. This general boundary condition consists of rough boundaries on velocity and Robin boundary condition on temperature. With the help of specific non-dimensional parameters, i.e., the slip-Darcy number and the Biot number that arise at lower and horizontal boundaries, we have been able to integrate 16 Rayleigh-Bard convection problems into one. Both parameters display a stabilising effect on the onset of convection. Utilising a minimal Fourier series representation, a generalised Lorenz model is derived. The solution of this Lorenz model is used to obtain the Nusselt number expression. The study also involves the usage of mono nanofluid and hybrid nanofluid of the type where spherical-shaped nanoparticles (alumina/copper) are dispersed into a binary base fluid mixture (water-EG). The thermophysical properties of the binary base fluid mixture and the corresponding nanofluids are calculated using mixture theory. Also, the thermophysical properties of mono nanofluid are derived and calculated from the mixture theory defined for the hybrid nanofluid type, which accounts for the correctness of the mixture theory used (verified using phenomenological laws and mixture theory for mono nanofluid). The papers main aim is to throw light on the ease rendered by the usage of general boundary condition, along with presenting a theoretical base for choosing the most suitable nanofluid concerning convection problems. An increase of 96.2984% in critical Rayleigh number is observed in the case of water-EG-alumina nanofluid when Biot number is increased from 10?3 to 106. Likewise, an increase of 107.223% in critical Rayleigh number for water-EG-alumina nanofluid is observed when slip-Darcy number is increased from 10?3 to 106. Limiting cases of the Rayleigh-Bard problem for 16 boundary conditions including free/rigid isothermal/adiabatic combinations at lower and upper boundaries are obtained, thereby presenting a strong validation for the study. Plots of stream function for different boundary conditions are included for a better physical understanding of the problem. 2025, Penerbit Akademia Baru. All rights reserved. -
Steering through the pandemic: narrative analysis of school leader experiences in India
The COVID ?19 pandemic has disrupted the regular functioning of schools. Transitioning to online learning posed significant challenges to all stakeholders in the educational system. The continued changes and challenges due to the pandemic require school leaders to make intuitive decisions. School leaders vision and leadership styles can considerably impact successfully managing crises and challenges. The current study looks at the lived experiences of eight school leaders working in India. The data collected using an interview guide was subjected to narrative thematic analysis. The interviews were designed primarily in an open-ended manner to captivate the story of their experiences. The results yielded an understanding of how school leaders navigated through multiple challenges such as transitioning online, attending to student needs, financial challenges adopting crisis and collaborative leadership. The results highlight various personal feelings and experiences that helped the school leaders to hold up during the crisis. School leaders lack training in crisis management, and their mental health needs are neglected. The paper calls for professional support for school leaders in managing professional and personal challenges. The article gives direction for school professionals on focus areas and requirements in Indian schools. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Steering through the pandemic: narrative analysis of school leader experiences in India
The COVID ?19 pandemic has disrupted the regular functioning of schools. Transitioning to online learning posed significant challenges to all stakeholders in the educational system. The continued changes and challenges due to the pandemic require school leaders to make intuitive decisions. School leaders vision and leadership styles can considerably impact successfully managing crises and challenges. The current study looks at the lived experiences of eight school leaders working in India. The data collected using an interview guide was subjected to narrative thematic analysis. The interviews were designed primarily in an open-ended manner to captivate the story of their experiences. The results yielded an understanding of how school leaders navigated through multiple challenges such as transitioning online, attending to student needs, financial challenges adopting crisis and collaborative leadership. The results highlight various personal feelings and experiences that helped the school leaders to hold up during the crisis. School leaders lack training in crisis management, and their mental health needs are neglected. The paper calls for professional support for school leaders in managing professional and personal challenges. The article gives direction for school professionals on focus areas and requirements in Indian schools. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Steering through the pandemic: narrative analysis of school leader experiences in India
The COVID ?19 pandemic has disrupted the regular functioning of schools. Transitioning to online learning posed significant challenges to all stakeholders in the educational system. The continued changes and challenges due to the pandemic require school leaders to make intuitive decisions. School leaders vision and leadership styles can considerably impact successfully managing crises and challenges. The current study looks at the lived experiences of eight school leaders working in India. The data collected using an interview guide was subjected to narrative thematic analysis. The interviews were designed primarily in an open-ended manner to captivate the story of their experiences. The results yielded an understanding of how school leaders navigated through multiple challenges such as transitioning online, attending to student needs, financial challenges adopting crisis and collaborative leadership. The results highlight various personal feelings and experiences that helped the school leaders to hold up during the crisis. School leaders lack training in crisis management, and their mental health needs are neglected. The paper calls for professional support for school leaders in managing professional and personal challenges. The article gives direction for school professionals on focus areas and requirements in Indian schools. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Steganography using Improved LSB Approach and Asymmetric Cryptography
Steganography deals with the craft of obscuring private data inside a spread media. In confidential data communication security is a vital issue. In this paper, we use a two-layer security. At first, data encryption is achieved by the method of RSA algorithm of asymmetric cryptography, and later the ciphered data is hidden into host image by an innovative embedding technique. To hide our ciphered data into host image, we modify the existing LSB technique and use a mapping function that ensures a secure and confidential image steganography resulting in a stego image. Here cryptography is blended with steganography and provides two level security in the confidential data transmission over the internet. 2020 IEEE.