Ontology based E-learning framework: A personalized,adaptive and context aware model

Multimedia Tools and Applications - Enhancing the degree of learner productivity, one of the major challenges in E-Learning systems, may be catered through effective personalization, adaptivity and...     

Stagnation flow of hybrid nanoparticles with MHD and slip effects

The flow of hybrid nanoparticles with significant physical parameters with different base fluids in the presence of Biot number, velocity slip, and MHD effects has not been explored so far, particularly for a circular cylinder. Therefore, the current report is presented to offer a numerical solution for hybrid nanoparticles with base fluids (water and ethylene glycerol) via a circular cylinder. The physical situation is interpreted in terms of partial differential equations and is converted into ordinary differential equations after applying the similarity transformation. The results are presented in both tabular and graphical forms. The impact of physical parameters on velocity distribution is examined through graphs. The comparative results of hybrid nanoparticles for distinct base fluids as ethylene glycol and water are proposed and the hybrid nanoparticles with base fluid water seems to be greater than that of the hybrid nanoparticles with base fluid EG. The temperature profile of hybrid nanoparticles is found to be a decreasing function with growth in velocity slip parameter but an opposite trend is noted in case of nanoparticles . The skin friction and Nusselt number augmented for the increase in magnetic field, velocity slip, and nanoparticle while it shows a decreasing trend toward thermal slip parameter. For the both cases, improvement in Biot number helps enhance the heat transfer constantly.     

Heat transfer analysis for particle–fluid suspension thermomagnetohydrodynamic peristaltic flow with Darcy–Forchheimer medium

This theoretical analysis explores the effect of heat and mass transfer on particle–fluid suspension for the Rabinowitsch fluid model with the stiffness and dynamic damping effects through Darcy–Brinkman–Forchheimer porous medium. In this study, we also incorporate slip and transverse magnetic field effects. Using low Reynolds number, to neglect inertial forces and to keep the pressure constant during the flow, channel height is used largely as compared with the ratio of length of the wave. A numerical technique is used to solve flow governing system of differential equations. Particular attention is paid to viscous damping force parameter, stiffness parameter, and rigidity parameter; also, the numerical data for thermal profile, momentum, and concentration distribution are presented graphically. Outcomes are deliberated in detail for different fluid models (thinning, thickening, and viscous models). It is found that velocity profile increases for greater values of viscous damping effect and stiffness and rigidity parameter for shear thinning, but conflicting comportment is showed for thickening nature model. Viscous dissipation effects increases the thermal profile for all cases of fluid models. The scope of the present article is valuable in explaining the blood transport dynamics in small vessels while considering the important wall features with chemical reaction characteristics. The current analysis has extensive applications in biomedical engineering field, that is, peristaltic pumps.     

Flow‐based electromagnetic‐type energy harvester using microplanar coil for IoT sensors application

Battery is the sole power source for Internet of thing (IoT) sensors. Due to limited shelf life, the batteries are required to be replaced intermittently. This periodic replacement of batteries is inflated in terms of both logistics and time. This article illustrates conceptual design, development, and characterization of a flow‐based electromagnetic‐type energy harvester (F‐EH) using microplanar coil for IoT sensors application. The F‐EH converts hydro energy into useful electrical energy utilizing electromagnetic transduction mechanism. The microfabrication and macrofabrication techniques adopted to manufacture harvester's components are presented. The F‐EH has been successfully characterized by laboratory scale experimental flow test loop commissioned for this work. Experimentation with associated uncertainty analysis prevails that at a matching impedance, the F‐EH can generate a 686 μW of maximum power at an operating flow rate of 12 L/min with an uncertainty of 8.1%.     

A critical review on self-lubricating ceramic-composite cutting tools

Self-lubricating ceramic cutting tools have recently gained considerable attention as the tool wear in cutting hard-to-cut materials greatly affects the production cost, integrity of the machined surface, and productivity. In an attempt to compile the progress made in this important research area, a critical review has been performed covering a range of aspects. These include the current research trends and the need for self-lubricating ceramic tools, identification of prospective high-temperature solid lubricants and their limitations followed by a presentation of recent experimental and numerical work conducted related to self-lubricant ceramic cutting tools. Various lubrication mechanisms involved in the cutting process are also examined to identify general tribological response under various tribo-systems, which is expected to provide useful directions for the researchers and cutting industry. The current and emerging synthesis techniques are discussed in detail and compared with respect to ceramic cutting tools. Finally, some research gaps and future directions are suggested that could lead to optimum design and development of innovative self-lubricating ceramic tools.     

On a class of branching problems in broadcasting and distribution

We introduce the following network optimization problem: given a directed graph with a cost function on the arcs, demands at the nodes, and a single source s, find the minimum cost connected subgraph from s such that its total demand is no less than lower bound D. We describe applications of this problem to disaster relief and media broadcasting, and show that it generalizes several well-known models including the knapsack problem, the partially ordered knapsack problem, the minimum branching problem, and certain scheduling problems. We prove that our problem is strongly NP-complete and give an integer programming formulation. We also provide five heuristic approaches, illustrate them with a numerical example, and provide a computational study on both small and large sized, randomly generated problems. The heuristics run efficiently on the tested problems and provide solutions that, on average, are fairly close to optimal.     

Big Data Analytics in Healthcare — A Systematic Literature Review and Roadmap for Practical Implementation

The advent of healthcare information management systems (HIMSs) continues to produce large volumes of healthcare data for patient care and compliance and regulatory requirements at a global scale. Analysis of this big data allows for boundless potential outcomes for discovering knowledge. Big data analytics (BDA) in healthcare can, for instance, help determine causes of diseases, generate effective diagnoses, enhance QoS guarantees by increasing efficiency of the healthcare delivery and effectiveness and viability of treatments, generate accurate predictions of readmissions, enhance clinical care, and pinpoint opportunities for cost savings. However, BDA implementations in any domain are generally complicated and resource-intensive with a high failure rate and no roadmap or success strategies to guide the practitioners. In this paper, we present a comprehensive roadmap to derive insights from BDA in the healthcare (patient care) domain, based on the results of a systematic literature review. We initially determine big data characteristics for healthcare and then review BDA applications to healthcare in academic research focusing particularly on NoSQL databases. We also identify the limitations and challenges of these applications and justify the potential of NoSQL databases to address these challenges and further enhance BDA healthcare research. We then propose and describe a state-of-the-art BDA architecture called Med-BDA for healthcare domain which solves all current BDA challenges and is based on the latest zeta big data paradigm. We also present success strategies to ensure the working of Med-BDA along with outlining the major benefits of BDA applications to healthcare. Finally, we compare our work with other related literature reviews across twelve hallmark features to justify the novelty and importance of our work. The aforementioned contributions of our work are collectively unique and clearly present a roadmap for clinical administrators, practitioners and professionals to successfully implement BDA initiatives in their organizations.