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Heat and mass transfer effects on non-newtonian fluid flow over an unsteady stretching surface with viscous dissipation and thermal radiation
This paper analyzes the flow, heat and mass transfer characteristics of non-Newtonian Casson fluid towards an unsteady permeable stretching surface. An external transverse magnetic field is applied normal to the sheet. The effects of viscous dissipation and thermal radiation are considered in energy equation. Rosseland approximation is used to model the radiative heat transfer. With the aid of similarity transformations, the unsteady boundary layer equations are transformed into a set of non-linear ordinary differential equations. Numerical solutions of resulting non-linear differential equations are solved by using efficient fourth-fifth order Runge-Kutta Feldberg method. The obtained numerical results are compared and found to be in good agreement with previously published results. Behavior of emerging parameters on velocity, temperature and concentration profiles are discussed and presented graphically. Further, variation of the reduced skin friction coefficient, Nusselt and Sherwood number against physical parameters in graphical and tabular form are presented and discussed in detail. It is found that the effects of thermal radiation and viscous dissipation are favorable for thickening the thermal boundary layer. 2018 Pushpa Publishing House, Allahabad, India. -
Heat and Mass Transfer Analysis of Newtonian and Non-Newtonian Nanofluids in The Presence of Motile Microorganisms
This dissertation deals with the analysis of heat and mass transfer in Newtonian and newlinenon-Newtonian nanoand#64258;uid in the presence of motile microorganisms. The major application of the and#64258;uids in heat and mass transfer process is its capability to conduct heat. Hence, the and#64258;uids act as a source that conducts heat and cools down the temperature of the appliance. Whereas, the capacity of heat conductance is low in case of regular and#64258;uids, hence the concept of nanoand#64258;uids was introduced whose thermal conductivity is more when compared to regular and#64258;uids. The high thermal conductivity of nanoparticles helps in conducting more heat and the property of and#64258;uid to and#64258;ow helps the nanoparticles to and#64258;ow all over the desired surface and conduct heat. During the process of nanoand#64258;uid and#64258;ow, the nanoparticles undergo random motion that is termed as Brownian motion and they also experience the thermophoretic force that causes the nanoparticles to move from hotter region to colder region. Further, the presence of nanoparticles would either result in sedimentation or formation a layer of nanoparticles over the surface. This layer of nanoparticles adhered to the surface creates corrosion. Hence, it is important to prevent the nanoparticles from forming its layer over the surface and also the sedimentation of nanoparticles must be avoided to have no blockages in the system. Hence in this regards, self propelled microorganisms newlineare allowed to swim in the nanoand#64258;uid which in turn constitutes bioconvection. Considering these assumptions, problems in this dissertation are modelled such that it deals with the analysis of bioconvection caused due to the swimming of microorganisms in the and#64258;ow newlineof nanoand#64258;uid. The mathematical models of the and#64258;ow, heat and mass transfer of Newtonian and non Newtonian nanoand#64258;uids are designed using the partial differential equations with various assumptions to achieve realistic results. -
Heat and mass transfer analysis of Casson-based hybrid nanofluid flow in the presence of an aligned magnetic field: An application toward mechanical engineering
This examination explores the flow of a hybridized nanofluid (HyNf) containing silica and tin oxide nanoparticles mixed with engine oil (EO/SnO2-SiO2). The flowing occurs via a permeable material constrained by a semi-infinite flat plate. The study takes into account various factors such as convective heat and mass transference, chemical reactions, the Dufour effect, the Lorentz force, thermal radiative fluxing, and radiative absorbing. The research involves converting the managing formulas of the flowing model into a dimensionless form and applying the regular perturbation procedure to find solutions for the rate of fluid flow, temperature, and species diffusion. The surface frictional factor, Nusselt quantity, and Sherwood quantity reflect the shearing stress, rates of heat transference, and rates of mass transport at the plate, respectively. An analysis is conducted on the impact of several factors, including the suction variable, magnetic variable, radiation-absorbing factor, Casson parameter, and Dufour number, on the flow and related quantities. This analysis is based on an examination of graphs and tables. The findings suggest that the heat transference rate in the Casson hybridized nanofluid is better than that in the mono nanofluid. It is exposed that the temperature reduces at the plate having improved frequency of oscillation and also fluid velocity declines for improving values of aligned magnetized field (Formula presented.), but it shows the reverse phenomenon with Gr1 and Gc1. IMechE 2024. -
Heat amd Mass Transfer Analyses of Nanofluid in a Multilayer Model
The study offers an in-depth exploration into the dynamics and properties of multilayered nanofluids and hybrid nanofluid flow in newlinedifferent geometries. The in-vestigation ranges from sinusoidal channels with micropolar hybrid nanoliquids to concentric cylinders that exhibit electrokinetic effects and rotating disks. Also, the DarcyForchheimer model is introduced to assess non-Newtonian and Newtonian fluid interplay, emphasizing the role of asymmetric slip conditions which reduces the fluid flow. Moreover, the study on bioconvection obtained newlineby addition of gyrotac-tic microorganisms which enhances mass and heat transfer in multilayer Newtonian fluid channels. Studies explain the importance of interfacial regions in achieving optimal system temperature. The subsequent study examines the two-layer hybrid nanofluid (HNF) with magnetohydrodynamic properties between two newlineidentical ro-tating disks. The governing equations of the mathematical models are explained using PDE and solutions are attained using numerical and semi-analytical methods such as the DTM and Range Kutta method. Further, the obtained results have been explained with the help of tables and graphs. The study reveals that the immisci-bility of the base fluids forms an interfacial layer, revealing that the addition of two different fluids restricts the fluid motion nearer to the interfacial region, maintaining an optimum temperature in the system. Collectively, these findings pave the way for advanced applications in industries like solar, nuclear, biomedical, and electronic cooling, promising enhanced newlineperformance and efficiency. -
Heart Disease PredictionA Computational Machine Learning Model Perspective
Relying on medical instruments to predict heart disease is either expensive or inefficient. It is important to detect cardiac diseases early to avoid complications and reduce the death rate. This research aims to compare various machine learning models using supervised learning techniques to find a better model that gives the highest accuracy for heart disease prediction. This research compares standalone and ensemble models for prediction analysis. Six standalone models are logistic regression, Naive Bayes, support vector machine, K-nearest neighbors, artificial neural network, and decision tree. The three ensemble models include random forest, AdaBoost, and XGBoost. Feature engineering is done with principal component analysis (PCA). The experimental process resulted in random forest giving better prediction analysis with 92% accuracy. Random forest can handle both regression and classification tasks. The predictions it generates are accurate and simple to comprehend. It is capable of effectively handling big datasets. Utilizing numerous trees avoids and inhibits overfitting. Instead of searching for the most prominent feature when splitting a node, it seeks out an optimal feature among a randomly selected feature set in order to minimize the variance. Due to all these reasons, it has performed better. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Heart Disease Prediction Using Ensemble Voting Methods in Machine Learning
Heart disease is the leading cause of mortality globally according to the World Health Organization. Every year, it results in millions of mortalities and thus billions of dollars in economic damage throughout the world. Many lives can be saved if the disease is detected early and accurately. The typical methods to predict or diagnosis heart diseases require medical expertise. Such facilities and experts are relatively expensive and not very commonly available in under developed and developing countries. Recent times, much research is done on leveraging technology for the prediction as well as diagnosis of heart diseases. Machine Learning techniques have been extensively deployed as quick, inexpensive, and noninvasive ways for heart disease identification. In this work, we present a machine learning approach in detecting heart disease using a dataset that contains vital body parameters. We used seven different models and combined them with Soft-Voting and Hard-Voting ensemble approaches to improve accuracy in 7-model and various 5-model combinations. The ensemble combinations of 5 models achieved the highest test accuracy score of 94.2%. 2022 IEEE. -
Healthy healthcare systems in India: A prognosis
India has been an emerging economy which has retained its second position in the global healthcare market that has been tackling its economic gaps, shifting demographics, thereby, facing a wide gap between the demand and supply of healthcare products and services due to technology and increasing cost. Affordable treatment facilities for the economically low strata is still a dream. The government scheme of "Swachh Bharat Abhiyan" and "Ayushman Bharat Yojna" are the steps to uplift the backward community and make all the facilities available to them at the lowest possible cost directly and indirectly. Hence, the objective of this research was to unfold the three pillars of Healthy Healthcare which revolves around healthcare systems in India, Healthcare Employees' wellbeing and resultant patient outcomes. This research also tried studying various interventions that can be taken to improve the present scenario of affordable and quality service to the needy people. Springer Nature Switzerland AG 2020. -
Healthcare cloud services in image processing
Technology has been fundamental in defining, advancing, and reinventing medicalpractises, equipment, and drugs during the last century. Although cloud computing is quite a newer concept, it is now one of the most often discussed issues in academic and therapeutic contexts. Many academics and healthcare persons are focused in providing vast, conveniently obtainable, and reconstruct assets like virtual frameworks, platforms, and implementations having lesser business expenditures. As they need enough assets to operate, store, share, and utilise huge quantity of healthcare data, specialists in the field of medicine are transferring their operations in the cloud. Major issues about the application of cutting-edge cloud computing in medical imaging are covered in this chapter. The research also takes into account the ethical and security concerns related to cloud computing. 2023, IGI Global. All rights reserved. -
HEALTH PSYCHOLOGY IN INTEGRATIVE HEALTH CARE
The 8th International Conference of Indian Academy of Health Psychology (ICIAHP 2023) gathered leading experts, researchers, and professionals to exchange insights and explore innovations in mental and physical well-being. Featuring workshops on trauma release, hypnotherapy basics, mindfulness-based CBT, and suicide prevention, ICIAHP offered a diverse learning experience. Distinguished speakers from national and international universities attended the conference. The conference catered to health psychology professionals, researchers, educators, and scholars. ICIAHP 2023 stood out for its comprehensive program, renowned speakers, and ample networking, providing a platform for holistic learning and collaboration. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Health Microinsurance-Challenges and Strategies
Golden Research Thoughts, Vol-2 (5), pp. 19-23. ISSN-2231-5063 -
Health informatics and its contribution to health sectors
In most developed countries, healthcare sectors take more than 10% of the GDP, and it is one of the most significant and most rapidly growing sectors globally. With such growth of the healthcare department, data management becomes challenging; a robust platform helps to address these challenges. Health Informatics (HI) is an upcoming development, an interdisciplinary field in healthcare sectors; it combines the Internet of Things (IoT) and Artificial Intelligence (AI) in the healthcare software, which helps boost the overall operational efficiency of the healthcare departments. These AI algorithms integrated into IoT devices help acquire, store, retrieve, and use health and medical-related data. Patient data are enormous in healthcare sectors, and it is required for various purposes by hospital administrators, insurance agents, doctors, nurses, and other health departments. Accessing and managing these datasets often becomes challenging; HI is one of those innovations that has helped address these challenges to a large extent. The chapter discusses informatics, related definitions, HI, and its relation with other disciplines. The chapter also provides an educational overview of the evolution of HI, different HI technologies, benefits and challenges of HI to its various stakeholders. It ends with some thoughts on HI's future growth. The Institution of Engineering and Technology 2023. All rights reserved. -
HEALTH EXPENDITURES AND HEALTH OUTCOMES IN CENTRAL EUROPE AND THE BALTIC REGION
In Central Europe and the Baltic region, healthcare expenditure has been growing slightly faster than across the euro area and in OECD countries. However, health outcomes as regards chronic diseases prove to be modest in the euro area and OECD countries compared to Central Europe and the Baltic region. Panel data analysis and country-specific regressions were conducted using World Bank data spanning from 2000 to 2019. Evidence suggests a significant correlation between private and current health expenditures and reduced mortality from chronic diseases in males, females and the total population across the panel, leading to improved longevity. Yet, public health expenditure does not correlate with a substantial reduction in mortality or a higher lifespan among the population, whether considered collectively or among males and females separately. Similarly, an increase in current health expenditure by one unit leads to significant reductions in mortality from non-communicable diseases: by 29 percent in the total population, 22 percent in females and 36 percent in males. Public health spending in Lithuania and Russia has been shown to decrease mortality from non-communicable diseases. Furthermore, chronic mortality is associated with a significant decline in labour productivity: by 42 percent in the total population, 40 percent in males and 45 percent in females. Therefore, interventions implemented through public health systems may reduce mortality from chronic conditions in the study countries. (2023), (Immanuel Kant Baltic Federal University). All Rights Reserved. -
Health Expenditure in Puducherry (U.T) A Study using National Health Accounts Framework
With the start of globalization, the Indian economy started experiencing a sudden growth and with the boom of various sector in the economy, the employment opportunity, income as standard of living started increasing. With the increase standard of living, there is an increase in demand for health care services. Health care plays an important role in the lives of the people. With government being welfare oriented every year the investment in health care increases and the private contribution to the health care sector is increasing at a higher pace. This study aims: (1) To quantify the extent of household expenditure on health by household characteristics in Puducherry; (2) To track the flow of resources in Health sector from different sources and present them in the form of accounting principles and (3) To develop a matrice format which facilitates the user to understand the sources of finances and uses of such finances on different item of expenditure. A primary data survey was conducted to capture the picture of household expenditure and the National Health Account matrices framework as prescribed by WHO was used in developing the health accounts matrices. The finding shows that majority of the household expenditure is made in purchasing medicine and other goods from the retail sector. Bulk of the spending is made in curative services. The expenditure flows to retail sale of medicines and drugs seems to be the major provider of services to the community. Households are the prominent sources for spending on health care. Out of the household surveyed only 2 to 3 per cent of the population would opt for health insurance. The present expenditure pattern seems to be shying away from other crucial functional elements of health care like Primary health care, Prevention of diseases, Public health and Promotive care. The study also finds a need to increase the awareness of Health insurance among the public and the need for more investment in health infrastructure as well as training of health personnel. -
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Health diagnosis of mango trees using image processing techniques
A Mango disease detection artificial intelligent model needs robust and effective newlinefeature extraction methods. The machine vision system has been designed for the newlineidentification of disease in plants from color leaf images. The research done proposes newlinenovel algorithms to extract color features Pseudo Color Regions and Texture Features newlineusing Pseudo Color Co-Occurrence Matrix. A new Mango dataset has been created and newlinealgorithms tested on it. An artificial intelligence model has also been created and tested on an existing disease dataset of Apple and Tomato plants. Results were compared with existing methods in the literature. The effectiveness of each statistical function was studied in classifying the pattern using a Support Vector Machine. For textures that are newlinedifferent like smooth new leaves, dry leaves, growth a Gray Level Co-occurrence based newlinestatistics was effective but values failed to discriminate in certain diseases. The proposed and implemented novel method which uses second-order statistics on a pseudo-color-based co-occurrence matrix has resulted in better classification. Pseudo Color Region feature is created using a novel intermediate data structure and found to be more effective than hue-based color features. It identifies dots, spots, patches and regions of different colors on the leaf and uses that as a feature vector to classify plant diseases. This generic method can be applied for early disease detection for plants and help farmers take corrective measures to avoid loss of yield. -
Health Care Still a Costly Affair: Covariates of Out-of-Pocket Expenditure on Health Care in India with Special Reference to Empowered Action Group States
This article investigates the covariates of out-of-pocket expenditure (OOPE) on health care, with a special focus on the Empowered Action Group (EAG) states of India. These states are economically weaker and vulnerable. For analysis, the study uses a nationally representative databasethe India Human Development Survey (IHDS I, 20042005 and IHDS II, 20112012)by applying the log-linear regression method. Four regression models have been specified in the article. The pooled regression method is applied to check the robustness of the models. Results identify that factors such as the location of the respondent, education, waiting time in hospitals, household expenditure per capita and the location of the hospital play a significant role in determining the OOPE on health care in India. Among other factors, waiting time in the hospital and the distant treatment location result in higher opportunity costs for better treatment facilities, hence increasing the burden on OOPE. The study concludes with suggestions based on these covariates, especially for the EAG states. 2024 Indian Institute of Health Management Research. -
HCI Authentication to Prevent Internal Threats in Cloud Computing
Cloud computing reduces physical resources and simplifies common management tasks. Over the past decade, cloud computing has become an important IT (information technology) industry, driving cost savings, flexibility, convenience, and scalability. Despite these advantages, many government organizations and companies are still cautious about using cloud computing. They continue to believe that the threats inherent in cloud computing technology are greater and deadly than traditional technologies. Cloud computing security threats typically include insider attacks, malware attacks, information leaks and losses, distributed denial of service, and application programming interface vulnerability attacks. Technical security improvements for virtual networks are actively researched, and many are working hard. But defending against internal attackers is more than just a technical solution but a complement to manuals and company policy. In reality, however, there are cases of damage by internal attackers, and the damage is getting bigger. Technically malicious internal attackers can relatively easily manipulate the control system and cause malfunctions. This paper provides comprehensive information about security threats in cloud computing, shows the severity of attacks by insiders, analyzes the latest authentication technologies for humancomputer interaction, and identifies the pros and cons. This shows how HCI (humancomputer interaction) technology can be applied to cloud computing management servers. The result is an innovative security certification model that can be applied. 2020, Springer Nature Switzerland AG. -
Hazard identification of endocrine-disrupting carcinogens (EDCs) in relation to cancers in humans
Endocrine disrupting chemicals or carcinogens have been known for decades for their endocrine signal disruption. Endocrine disrupting chemicals are a serious concern and they have been included in the top priority toxicants and persistent organic pollutants. Therefore, researchers have been working for a long time to understand their mechanisms of interaction in different human organs. Several reports are available about the carcinogen potential of these chemicals. The presented review is an endeavor to understand the hazard identification associated with endocrine disrupting carcinogens in relation to the human body. The paper discusses the major endocrine disrupting carcinogens and their potency for carcinogenesis. It discusses human exposure, route of entry, carcinogenicity and mechanisms. In addition, the paper discusses the research gaps and bottlenecks associated with the research. Moreover, it discusses the limitations associated with the analytical techniques for detection of endocrine disrupting carcinogens. 2024 Elsevier B.V. -
Has Indias Employment Guarantee Program Achieved Intended Targets?
This paper explores the performance of the worlds largest employment guarantee program, the Mahatma Gandhi National Rural Employment Guarantee Schemes in India, both nationally and through a sub-national-level comparison based on key performance indicators viz. (i) financial indicators, (ii) physical performance indicators, and (iii) inclusiveness indicators. The paper is based on administrative data taken from the Ministry of Rural Development from 2006 to 2019. Despite sharp increases in fund allocation, total expenditures, and utilization rates, there was deceleration in majority of physical performance indicators after 2016, including total person-days employment and person-days of employment per household, with wide variation in sub-national level implementation capabilities. The finding also rejects the falsity of saturation of MGNREGA work in the rural areas, which is reflected in a strong positive correlation between fund allocation and employment generation. Its broader objective of social safety net for vulnerable people in rural areas shows an achievement, although with some gaps in implementation. JEL classification: H53, J43, P25 The Author(s) 2021. -
Harnessing transition metal oxide?carbon heterostructures: Pioneering electrocatalysts for energy systems and other applications
Exponential demand for energy resources and fossil fuel substitution with green alternatives are essential to bringing sustainable development and a solution to the energy crisis. Transition metal oxides (TMOs) and their composites (TMOCs) as promising electrocatalysts to develop potential energy conversion and storage devices contribute to the solution to this crisis. The productivity of green fuels such as hydrogen from water-splitting reactions, the efficiency of energy storage and harvesting devices including supercapacitors and batteries, and the performance of electrochemical sensors can be remarkably enhanced with TMOs and their composites. Excellent electrochemical attributes, stability, abundant reserves, low cost, environment-friendly, and low toxicity make TMOs and their composites an excellent choice. The tunability of the physical and chemical properties of TMOs makes them attractive for research in designing different energy storage devices. This review presents a concise overview of the unique physical and electrochemical aspects of various TMOs and TMOCs, such as spinels, perovskites, and TMO-integrated carbon-based compounds, and their relevance for specific applications, emphasizing energy-related fields. The recent research advancements of TMOs-based functional materials for emerging applications, such as water splitting, fuel cells, supercapacitors, batteries, and sensing, are discussed. This review also highlights the advantageous properties and pertinent fabrication methods of TMOs and TMOCs for electrocatalysis, along with the methods to enhance their electrocatalytic abilities, which improve the overall efficiency of the desired applications. 2024