This paper presents a layered hierarchy that depicts the progressive relationship between data, information, knowledge, and wisdom. To begin with, data is gathered and organized into information. ...Information is gathered, filtered, refined, and put through an investigation process to create knowledge. Wisdom is attained after knowledge discovery through the process of filtration and aggregation through experience. The layered hierarchy in the domain of e-healthcare necessitates higher scheduling costs for data collection, processing wisdom, and management, which is also an insecure and untrustworthy process for progressive medical service. The medical industry faces a difficult problem in providing collected data integrity, information reliability, and knowledge trustworthiness for the service of progressive medical relationships in the face of an increasing number of day-to-day records. The blockchain consortium hyperledger (fabric) has been used in this paper to act as a bridge that bridges the gap between electronic data, information, knowledge, and wisdom (DIKW) movement and processes by enabling the process of the layered hierarchy of schedule information and management and providing security and transparency. For e-healthcare information management and privacy, the DIKW-ledger, such as patients’ consultancy information, availing medical services, personal records, appointments, treatment details, and other health-related transactions, a consortium hyperledger fabric-enabled efficient architecture is proposed. This proposed architecture creates two networks: a public network for medical stakeholders to exchange and agree on specific medical activities before being preserved on distributed storage (read-only after record registration) and a private network for complete DIKW process scheduling and management. We designed and created smart contracts for this purpose, as well as use-case diagrams to describe the overall execution process. The proposed architectural solution provides more efficient information integrity, provenance, and storage procedures to immutably preserve the medical ledger in a permissioned hash-encrypted structure.
Owing to the sensitive nature of healthcare data, the aforementioned approach to transferring patient data to central servers creates serious security and privacy issues. In addition, blockchain ...distributed ledger technology has introduced immutable storage and decentralized data management capability, which handles a large number of distributed nodes of E-Healthcare transactions via a serverless network, but in a limited manner because of blockchain-enabled resources. In this scenario, the medical industries are concerned about constituting an innovation in health information preservation and exchanging service delivery protocols without the connectivity of an untrusted third-party infrastructure. In this study, we proposed a blockchain hyperledger fabric-enabled consortium architecture called BIoMT, which provides security, integrity, transparency, and provenance to health-related transactions and exchanges sensitive clinical information in a serverless peer-to-peer (P2P) secure network environment. A consensus is designed and created to reduce the rate of blockchain resource constraints on the Internet of Medical Things (IoMT). The privacy of individual health transactions before sharing is protected using the NuCypher Re-Encryption mechanism, which increases security and provides medical ledger integrity and transparency. Smart contracts are created and deployed to automate device registration, exchange transactions, and ledger preservation in immutable storage (filecoin) after cross verification and validation. The experimental results show that the proposed BIoMT reduces the computational cost by 26.13%, and the robust medical node generation increases to 60.37%. Thus, only 31.79% and 74.21% of IoMT-related information and serverless P2P network usage are maintained and saved, respectively.
PurposeThis research investigates the effects of multidimensional brand experiences (i.e. behavioral, intellectual, affective and sensory) on brand authenticity and brand love from the Asian ...consumers' perspective.Design/methodology/approachThis research collected primary data from 418 consumers on global brands, and it tested the proposed hypotheses by using partial least squares structural equation modeling (PLS-SEM).FindingsThe findings indicate that sensory and affective experiences have direct significant impacts on brand love, while intellectual and behavioral experiences have nonsignificant impacts on brand love. Overall, intellectual, behavioral, affective and sensory experiences positively influence brand authenticity, which in turn have substantial positive impacts on brand love.Research limitations/implicationsThis study investigated consumer behavior in a broader sense, and consumers from 13 Asian countries participated in this research. Future research may collect data on a larger scale from Asian countries to generalize the results.Practical implicationsBy following brand authenticity as an essential positioning tool and implementing several experiential marketing strategies, global managers can develop brand-loving consumers in Asia.Originality/valueUnder the parasol of attribution theory, this research explores the relationships among the multidimensional brand experiences, brand authenticity and brand love from the Asian perspective.
Purpose
Authenticity has become increasingly dominant in business practices, particularly in branding and corporate social responsibility (CSR) activities, as consumers want it in all aspects of ...their lives. Thus, the purpose of this study is to examine the role of perceived CSR authenticity in predicting perceived brand loyalty (i.e. brand trust, positive word of mouth PWOM) via perceived brand authenticity by considering the moderating effects of brand image on perceived brand authenticity and loyalty to determine its influence in the global branding context.
Design/methodology/approach
Using a non-probability convenience sampling technique, this study received 817 responses from consumers who regularly used global brands. Finally, this research examined 734 responses to test the proposed hypotheses using structural equation modeling.
Findings
This study discovered that perceived CSR authenticity strengthened perceived brand authenticity, which fostered perceived brand loyalty by enhancing brand trust and motivating consumers to spread PWOM about global brands. Similarly, perceived CSR authenticity directly influenced perceived brand loyalty by enhancing brand trust but did not affect PWOM. Likewise, the moderating effect of brand image was significant in fostering perceived brand loyalty by enhancing brand trust, but it had no effect on PWOM. In contrast, the brand image had a significant negative effect on perceived brand authenticity.
Practical implications
This research offered many insightful suggestions to global managers in the manufacturing and service industries that might assist them in designing and implementing several branding strategies to achieve corporate objectives.
Originality/value
This novel research contributes to the attribution theory by examining consumers’ perceptions of CSR authenticity, brand image, brand authenticity and brand loyalty from the global branding perspective.
Display omitted
•Environmental effects of political stability and income inequality.•Second-generation panel data methods are utilized for four South Asian countries.•Political stability and ...renewable energy improve environmental quality.•Income inequality and urbanization worsen the ecological footprint.
South Asian economies have experienced considerable growth over the last two decades, which has brought with it a number of problems. Despite the rapid growth, income inequality has increased in South Asia and political instability continues mainly due to territorial disputes between Pakistan and India. In addition to these factors, the increase in population and energy consumption has also contributed to the environmental problems in South Asia. Therefore, there is a need to analyze the role of income inequality and political stability in environmental degradation and thus take measures to prevent irreversible environmental consequences. In this background, this study examines the role of income inequality and political stability on environmental degradation in four South Asian countries (Pakistan, India, Sri Lanka, and Bangladesh). For this purpose, the study employs second-generation panel data approaches on a Stochastic Impacts by Regression on Population, Affluence, and Technology model (STIRPAT). Based on annual data for the period 2002–2016, the empirical results show that economic growth, income inequality, urbanization, and financial development increase the ecological footprint, while political stability and renewable energy utilization help to reduce environmental degradation. The findings of the panel causality test also suggest unidirectional causality from urbanization, renewable energy, economic growth, and income inequality to ecological footprint. According to these findings, ensuring political stability, reducing income inequality, and promoting renewable energy are essential policy instruments for sustainable and green development in four South Asian countries.
Abstract
Nanofluids are implementable in a variety of applications, such as heat exchangers, the healthcare sector, the cooling of various devices, hybrid-powered machines, microelectronics, power ...plants, chemical processes, astronomical technology, cancer treatment, etc. Nanofluids also have enhanced heat transmission and thermal efficiency. The heat radiation of nanoparticles and the natural-convective flow of electrically conducting nanofluids over the rotating disk using Darcy Forchheimer’s porous media, thermal radiation is investigated in this paper. The nanoparticles titanium dioxide and single-walled carbon nanotubes are taken into account with base fluid water. The main goal of this investigation is to enhance heat transfer in nanofluids. The mathematical solution for the model has been obtained through the utilization of cylindrical coordinates. The flow model, which forms the basis of the investigation, is constructed around partial differential equations (PDEs). To address the inherent nonlinearity of these PDEs, physical similarities are employed to transform them into ordinary differential equations (ODEs). Subsequently, the fourth-order Runge–Kutta technique is employed via Matlab to solve these ODEs. The graphical examination of the velocities and temperature with various parameters is an exquisite display of scientific artistry. The magnetic field component is anticipated to exhibit an inverse correlation with velocities, while the temperature profile is expected to surge with the rise of the nonlinear mixed convection parameter. Additionally, the skin friction and Nusselt number are meticulously computed and presented in a tabular format, adding a touch of elegance to the already breathtaking analysis. By boosting the radiation parameter, the Nusselt value declined. Moreover, it is observed that the nanofluids having a laminar nanoparticle shape have a greater heat transfer rate.
In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based data are captured through drones and transmitted to the fog nodes. ...The main objective here is to enable process and schedule, to investigate individual captured entity (records) and to analyze changes in the blockchain storage with a secure hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. The proposed blockchain mechanism is also investigated for analyzing the fog-cloud-based stored information, which is referred to as smart contracts. These contracts are designed and deployed to automate the overall distributed monitoring system. They include the registration of UAVs (drones), the day-to-day dynamic captured drone-based images, and the update transactions in the immutable storage for future investigations. The simulation results show the merit of our framework. Indeed, through extensive experiments, the developed system provides good performances regarding monitoring and management tasks.
Display omitted
•Study examines wind and solar energy impact on environmental quality.•Wind and solar energy production has a negative effect on the ecological footprint.•Real GDP has a positive ...impact on ecological footprint.
The motivation of the present study is to evaluate the effect of wind and solar energy production and economic development on environmental quality in 43 countries covering the period of 1990–2017. The study uses annual data for real GDP, real trade, energy intensity, urbanization, foreign direct investment, ecological footprints, and wind and solar energy production. For econometric analysis, common correlated mean group (CCE-MG), cross-section-distributive lag (CS-DL), and cross-section autoregressive-distributive lag (CS-ARDL) approaches are employed. The outcomes show that real GDP has a significantly positive influence on ecological footprint. At the same time, wind and solar energy negatively and significantly influence ecological footprint. It is argued that a 1 % increase in wind and solar energy reduces ecological footprint by 3.1 % and 2.9 %, respectively. For policy recommendations, the study recommended that wind and solar energy resources may become more noticeable for electricity purposes despite rising investments in these energy resources. Indeed, the share of wind and solar energy production is limited and dominated by non-renewable energy resources, so low-carbon energy resources might be encouraged.
X-ray diffraction (XRD) is an important and widely used material characterization technique. With the recent development in material science technology and understanding, various new materials are ...being developed, which requires upgrading the existing analytical techniques such that emerging intricate problems can be solved. Although XRD is a well-established non-destructive technique, it still requires further improvements in its characterization capabilities, especially when dealing with complex mineral structures. The present review conducts comprehensive discussions on atomic crystal structure, XRD principle, its applications, uncertainty during XRD analysis, and required safety precautions. The future research directions, especially the use of artificial intelligence and machine learning tools, for improving the effectiveness and accuracy of the XRD technique, are discussed for mineral characterization. The topics covered include how XRD patterns can be utilized for a thorough understanding of the crystalline structure, size, and orientation, dislocation density, phase identification, quantification, and transformation, information about lattice parameters, residual stress, and strain, and thermal expansion coefficient of materials. All these important discussions on XRD analysis for mineral characterization are compiled in this comprehensive review, so that it can benefit specialists and engineers in the chemical, mining, iron, metallurgy, and steel industries.
With the wide application of Internet-of-Medical-Things (IoMTs) or sensor nodes which equipped with sensors. These networked sensors are used to gather enormous data from different smart healthcare ...applications, and this collected data process for making appropriate decisions. Edge computing is an efficient platform that provides computational resources to collect sensor data. In the meantime, intelligent and accurate resource management by Artificial Intelligence (AI) has become the center of attention, especially in healthcare systems. With the help of AI, IoMT based healthcare devices will remarkably enhance the computational speed and range. But the challenging issue in these energy-hungry, short battery life, and delay intolerant portable devices is inappropriate and inefficient classical trends of fair resource allotment. Thus, this paper proposes Computation Offloading using Reinforcement Learning (CORL) scheme to minimize latency and energy consumption. We first formulate the problem as a combined latency and energy cost minimization problem, satisfying the lack of limited battery capacity and service latency deadline constraints. Moreover, proposed algorithm search optimal available resources node to offload task towards the trade-off between energy and latency. The experimental results show the benefits of the proposed scheme in terms of saving energy, minimizing latency, and maximum utilization of node resources in edge-enabled sensor networks. We are using an iFogSim simulator to validate the proposed scheme under realistic assumptions.
PDF
