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Machine Learning Observation on the Prediction of Diabetes Mellitus Disease
Diabetes disease has become as one of the common syndromes in many of the age groups. Diabetes can result in high blood sugar levels, a heart attack, or heart disease. This is one of the fastest developing illnesses, and it requires regular care. After seeing the doctor and being diagnosed, the patient is typically compelled to obtain their reports. Because this procedure is time-consuming and costly, we have the option of using ML approaches to solve this problem. Our research aims to foster a framework prepared to do all the more precisely foreseeing a patient's diabetes risk level. To develop models, classification methods such as Logistic Regression, K-Nearest Neighbor, Support Vector Machine, and Random Forest Classifier are employed. The results indicate that the techniques are quite accurate. The result showed that the prediction with the Logistic Regression model acquired the highest accuracy. 2023 IEEE. -
Mixed convection 3D radiating flow and mass transfer of eyring-powell nanofluid with convective boundary condition
Three-dimensional mixed convection flow, heat and mass transfer of Eyring-powell fluid over a convectively heated stretched sheet is inspected in this paper. The encouragement of Brownian motion, thermophoresis, convective condition and thermal radiations are accounted. Appropriate transformations are used to reduce the principal PDE's into set of coupled highly nonlinear ODE's which are then solved numerically using RKF fourth-fifth order method. The consequence of several parameters on flow, heat and mass transfer characteristics are deliberated with the help of graphs and tables. It is observed that the temperature and concentration profiles diminish for higher values mixed convection parameter. Further, the temperature and its related boundary layer thickness is increases with increasing the Biot number and thermal radiation effects. 2018 Trans Tech Publications, Switzerland. -
Magnetohydrodynamic flow of williamson nanofluid due to an exponentially stretching surface in the presence of thermal radiation and chemical reaction
A steady MHD boundary layer flow of Williamson nanofluid over an exponential stretching surface through a porous medium is considered. The effects of Brownian motion and thermophoresis have examined in the energy transport equation. The influences of solar radiation and chemical reaction are taken into the account. The governing boundary layer equations with the boundary conditions are transformed into nonlinear ordinary differential equations with the help of selected exponential type of similarity variables. They are then solved numerically using well-known Shooting technique along with Runge-Kutta-Fehlberg method. The numerical results are presented through graphs and a table to discuss the characteristics of different flow fields versus pertinent parameters. Comparisons with previously published work have been conducted and the results are found to be in good agreement. It is found that temperature field is enhanced for the larger Brownian motion, thermophoresis parameter and radiation parameter effects. 2017 by American Scientific Publishers. All rights reserved. -
Play and Play Spaces for Global Health, Happiness, and Well-Being
Play has a significant role in an individuals learning and holistic development. Play and recreation are a need and right. Research on play indicates that the significance of play is neglected among the current generation. Play spaces are shrinking, and physical play is becoming extinct in most communities. This current scenario may or have led to poor physical and mental health outcomes. The proposed book chapter aims to present play and play spaces in physical and mental health. The literature of play theories in child development shows the role of play in socioemotional, physical, and cognitive development. The current paper brings together literature on play across the lifespan, highlighting how play and recreation impacts children, youth, adults, and older adults physical and mental health. The change in lifestyle patterns has contributed to the neglect of play and recreation. The paper throws light on the need for the attention of professionals and policymakers for interventions and advocacy at both local and global levels in promoting play and preserving natural play spaces. The Editor(s) (if applicable) and The Author(s), under exclusive license to Taylor and Francis Pte Ltd. 2022. -
Advancing Image Security Through Deep Learning and Cryptography in Healthcare and Industry
Securing electronic health records (EHRs) in the Internet of Medical Things (IoMT) ecosystem is a key concern in healthcare due to the sector's differed environment. As the evolution of technology continues, ensuring the confidentiality, integrity, and accessibility of EHRs becomes more and more challenging. To enhance the confidentiality of healthcare picture data, this study explores the combined use of deep learning and cryptography methods. Through the utilization of weight analysis for improving encryption strength and the combination of chaotic systems to generate undetectable encryption patterns, it explores how deep neural networks can be modified for use in encryption. It also provides a survey of the present scenario of deep learning-based image detection of anomalies methods in working environments, such as network typologies, supervision levels, and assessment norms. Techniques in cryptography provide an effective means to protect confidential medical picture data while it's being transmitted and stored. Deep learning, on the other hand, has the ability to entirely change cryptography by providing robust encryption, resolution augmentation, and detection capabilities for medical image security. The paper outlines future research approaches to overcome these problems and tackles the opportunities and obstacles in medical image cryptography and industrial picture anomaly detection. Through this work, picture privacy in the healthcare and industrial sectors is advanced, opening the door to enhanced privacy, integrity, and availability of vital image data by overcoming the gap between deep learning and cryptography. 2024 IEEE. -
Solution of a dengue fever model via fractional natural decomposition and modified predictor-corrector methods
In this paper, we solved a model of a well-known infectious disease called dengue fever via fractional natural decomposition and modified Predictor-Corrector (PC) methods. A study of the dengue epidemic in the Cape Verde Islands off the coast of West Africa in 2009 has been resumed here for a better understanding of the results. The results are obtained using Liouville-Caputo and new generalized Caputo-type fractional derivatives. The numerical simulations are presented for various orders of given derivatives. Existence and uniqueness analysis of the given problem are also performed in the new generalized Caputo sense. The explored results are verified using figures. The main target of this paper is to explore the different dynamics of the given dengue fever model via two types of fractional numerical algorithms. 2024 World Scientific Publishing Company. -
Sustainable Computing: A Determinant of Industry 4.0 for Sustainable Information Society
Rapid advancement in technology and continuous environmental degradation have attracted the attention of practitioners toward sustainable solutions. This study intends to promote Industry 4.0 information society research by comprehending sustainable ICT adoption in businesses to promote sustainable information society (SIS). Further, it extends the theory of planned behavior model and deploys a quantitative research approach. The findings from PLS-SEM confirm the perceived environmental responsibility (PER), a precursor for attitude (ATT), perceived behavioural control (PBC), and subjective norm (SN). Further, there is a significant positive influence of ATT, PBC, and SN on the adoption intention of sustainable ICT practices followed by the effect of adoption intention on sustainable information society (SIS). This study bridges the literature gap through a novel attitude behavior gap model and provides a possible understanding of how businesses might contribute to the creation of sustainable development and information society. 2022 Nishant Kumar et al. -
Characteristic Mode Analysis of Closed Metal Geometric Ring Shapes
In this study, the characteristic mode theory is used to better explain the physical behavior of a few simple closedshaped geometries. The bandwidth coverage, resonant behavior, and modal current distributions for several ringshaped geometries are shown and discussed. It has been demonstrated that the triangular, rectangular, and square ring geometries can result in multi-band performance, whereas the hexagonal, circular, square, and triangular rings are promising candidates for circularly polarized antenna designs. 2024 IEEE. -
Characteristic Mode Analysis of Metallic Automobile Logo Geometry
This paper presents a characteristic mode analysis of a few popular automobile logo geometries. It is performed to get an insight into the physical behavior of those geometries which can be employed as a radiating element, such as an antenna. Such an analysis helps design multi-band and multi-mode antennas suitable for 5G sub-6 GHz bands. The resonant behavior, bandwidth capability, and modal current distribution analysis are presented for various modes of different automobile logo geometries, demonstrating that Audi, Suzuki, and Volkswagen logos show multi-band performance. Moreover, due to having symmetric modes, the BMW logo was found to be suitable for designing a circularly polarized antenna. 2023 IEEE. -
Environmental Concern in TPB Model for Sustainable IT Adoption
Rapid advancement in technology and continuous environmental degradation has attracted the attention of practitioners toward sustainable solutions. This study aims to investigate educated millennial beliefs and behavior toward sustainable IT practices. The Theory of Planned Behavior (TPB) model deployed in the study was extended through perceived environmental responsibility. A survey was conducted to examine the sustainable IT adoption behavior of millennial in the National Capital Region, Delhi India. Variance based partial least square structure equation modeling was employed to evaluate the hypothesized model. Findings of the study confirm environmental concern (ER) a precursor for attitude (ATT), perceived behavioral control (PBC), and subjective norm (SN). Further, there is a significant positive influence of ATT, PBC, and SN on the adoption intention of sustainable IT practices, followed by the effect of adoption intention on actual adoption behavior. Study disseminates valuable insights to policymakers and marketers to formulate strategies and policies to attain sustainability through sustainable IT practices. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Decision-making using regression analysis: a case study on Top Tier Holidays LLP
Research methodology: This study aims to investigate the factors that contribute to the overall tour experience and services provided by Top Tier Holidays. The study is mixed in nature, and the researchers have used analytical tools to analyse the data factually. Multiple regression using MS Excel is used in the study. Case overview/synopsis: This case is based on the experiences of a real-life travel and tour company located in New Delhi, India. The case helps understand regression analysis to identify independent variables significantly impacting the tour experience. The CEO of the company is focused on improving the overall customer experience. The CEO has identified six principal determinants (variables) applicable to tour companies success. These variables are hotel experience, transportation, cab driver, on-tour support, itinerary planning and pricing. Multiple regression analysis using Microsoft Excel is conducted on the above determinants (the independent variables) and the overall tour experience (the dependent variable). This analysis would help identify the relationship between the independent and dependent variables and find the variables that significantly impact the dependent variable. This case also helps us appreciate the importance of various parameters that affect the overall customer tour experience and the challenges a tour operator company faces in the current competitive business environment. Complexity academic level: This case is designed for discussion with the undergraduate courses in business management, commerce and tourism management programmes. The case will build up readers understanding of linear regression with multiple variables. It shows how multiple linear regression can help companies identify the significant variables affecting business outcomes. 2023, Emerald Publishing Limited. -
Blockchain Integrated Pharmaceutical Cold Chain: An Adoption Perspective
A complex and sensitive chain needs to be appropriately maintained to manage public health and people's lives. This is especially true of the cold pharmaceutical chain. The primary objective of this study is to explain how blockchain adaption might meet a pharmaceutical cold chain's requirements. A comprehensive technological adoption model, partial least square structural equation modeling, and a quantitative cross-sectional survey approach were utilized to identify stakeholder adoption intentions toward a blockchain-enabled cold supply chain. This study provides evidence that blockchain technology has the potential to support the objectives of the cold pharmaceutical chain. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Impact of Mahatma Gandhi National Rural Employment Guarantee Act on Rural Credit System in India: A Standard Logit Difference in Difference Approach
The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) of India is one of the most extensive social safety nets programs in the developing world. The initiative attempts to enhance rural livelihoods in India by lowering rural poor vulnerability and misery. The programs nature and extent of execution vary from state to state. Using panel data sets from the Indian Human Development Survey (IHDS), which covering India for two waves, 200405 and 201112. We used a quasi-experimental approach, such as the difference-in-difference technique of effect evaluation, to quantify the programs influence on rural families credit and debt structures. The empirical analysis shows evidence of changing the behavior of taking loans from formal sources among non-poor households actively participating in the MGNREGA program. But the difference-in-difference results shows that among poor households participating in the MGNREGA scheme, the tendency to depend on formal sources to take loans is still insignificant. That means informal lending sources are still more prevalent among poor people. This tendency has not changed even after the initiation of this program. The article finishes with policy recommendations for successfully targeting the program, notably the social safety net benefits to disadvantaged households in India. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Characteristic Mode Analysis of Fashion Brands Conductive Logos as Potential Radiators
A few popular fashion brand logos, which can be employed as potential radiating elements, are investigated in this paper based on the theory of characteristic mode (TCM). Such an analysis would further help design multi-band wearable antennas within the frequency range from 1 to 6 GHz. The resonant behavior and bandwidth capability for various modes are presented and discussed. It is observed that all the studied logos demonstrate a first resonant frequency around 1.5 GHz, while both Lacoste and Louis Vuitton logos show wider modal bandwidths capabilities. 2023 IEEE. -
Blockchain Integrated Retail Logistics Chain: An Adoption Perspective
The task of managing public health and safety is a multifaceted and delicate one that demands the careful upkeep of numerous processes and systems, with a particular emphasis on cold chain logistics. The primary objective of this research is to investigate how blockchain technology can meet the needs of a retail cold chain. To accomplish this goal, we employed a comprehensive technological adoption model, partial least squares structural equation modeling, and a quantitative cross-sectional survey approach to ascertain stakeholder adoption intentions toward a blockchain-enabled cold supply chain. Our findings suggest that blockchain technology has the capacity to effectively facilitate the goals of the retail cold chain. 2024 IEEE. -
Blockchain for customer transparency in e-commerce a survival of fittest not fastest
Blockchain has been envisioned as the most disruptive technology in the landscape of ecommerce. There has been an array of challenges for e-commerce retailers to handle like transparency, immutability, reliability and disintermediation. The paper is an attempt to understand consumer acceptance towards new technology where the primary focus would be transparency and plans for human salvation by combating the environment and ethical challenges. The study emphasises the prospective use of blockchain technology in ecommerce industry which has been coupled with the vagueness of these issues. Unified theory of acceptance and use of technology (UTAUT) has been used as the base model to understand the consumer behaviour towards using blockchain technology as a new platform with special reference to fashion apparel sector. Providing traceability of product with an objective of consumer transparency in this mould will change the way of doing online shopping and will have more onus on retailers. Copyright 2023 Inderscience Enterprises Ltd. -
Use of blockchain technology for smart health-care services: a critical perspective of ethnic minority group
Purpose: The essence of blockchain governance is a far departure from the cryptocurrency or Bitcoin that has led to innovation and changing the outline of medical services. The major challenge in medical services is the lack of accessibility of medical services and lack of awareness. A large group of the population belonging to an ethnic minority has a high rate of complications, re-operation and graft rejection. To connect with a minority group and address privacy and safety issues, blockchain-based e-health-care services have massive potential in the medical industry, especially from the perspective of the social aspect. Design/methodology/approach: The study proposed a framework that describes the complex interplay of different stated factors, including perceived ease of use, trust, perceived usefulness and perceived security and privacy. The paper uses structural equation modeling to understand the ethnic minority groups readiness to adopt blockchain-based e-health-care services. Findings: It was found that all the direct relationships between variables are supported by the findings and have a significant positive relationship with the adoption intention. The tested framework will help regulatory bodies and marketers to develop support health-care service mechanisms for ethnic minority groups by addressing their issues related to security and privacy. Originality/value: Blockchain-based e-health-care services have massive potential in the medical industry, although, its actual diffusion has not been explored much, with particular reference to an ethnic minority group. This study will explore the diffusion of smart health-care services with respect to ethnic minority group. 2023, Emerald Publishing Limited. -
Ensuring robust and secure supply chain: Deploying blockchain
Transparency, visibility, security, source-to-store traceability, and rising customer expectation are the critical points in the retail supply chain. The global supply chain involves a nexus of manufacturers and suppliers who urge for a robust network addressing the above challenges in the supply chain. A better provenance tool can benefit retailers, as customers are more concerned about the retail journey of the product start from its origin. Within the small span since its inception, blockchain has revolutionized the businesses and shown promising result in reshaping the supply chain. Blockchain in retail can provide evidence for the authenticity of product, tacking details for reliable retail delivery and enriching customer experience through product provenance. This chapter aims to explain to retailers the challenges, opportunities, and potential application of blockchain in the retail supply chain. 2024, IGI Global. All rights reserved. -
The unique risk factor profile of triple-negative breast cancer: a comprehensive meta-analysis
Background: Triple-negative breast cancer (TNBC) has a poor prognosis compared with other breast cancer subtypes. This systematic review and meta-analysis examines whether known risk factors for breast cancer are also associated with TNBC in adult women. Methods: EMBASE, Medline, SCOPUS, and gray literature were queried with no limit on the date or language of publication. The exposures of interest included parity, breastfeeding, duration of breastfeeding, age at menarche, age at first live birth, oral contraceptive (OC) use, duration of OC use, use of menopausal hormone therapy (MHT), family history, body mass index (BMI), alcohol use, smoking, and breast density. The main outcome of interest was TNBC. Study quality was determined using the Newcastle-Ottawa scale for case control studies and cohort studies. We estimated weighted odds ratios from random effects models to study the exposureoutcome associations. Protocol was registered under the number: PROSPERO 2021 CRD42021254594. Results: Thirty-three studies were included. Family history, longer duration of OC use, and higher breast density were significantly associated with increased risk for TNBC, whereas later age at menarche, later age at first birth, and breastfeeding were protective against TNBC. Parity, MHT, alcohol, smoking, and BMI were not significantly associated with TNBC overall, but higher parity was associated with higher risk among Black women. Conclusion: Our findings highlight that TNBC has a distinct risk factor profile compared with overall breast cancer. This can be the foundational work in identification of actionable TNBC risk factors to improve prevention and early detection of these poor prognosis breast tumors. The Author(s) 2024. -
