Some Aspects of Stability and Nanophase Formation in Quasicrystals during Mechanical Milling

Non-equilibrium processing and other related techniques can activate quasicrystalline structures to a higher energy level and enable them to attain various stable/metastable structures. During mechanical milling of quasicrystalline alloys, the stability of the complex structures is of immense importance from a scientific and technological point of view. The evolution of nanoquasicrystalline, nanocrystalline, and amorphous phases and their composites has been observed in the course of milling. The experimental results for mechanical alloying of elemental powders (required for the synthesis of quasicrystals) and mechanical milling of quasicrystals are discussed. The salient features observed in quasicrystals during other non-equilibrium processing are highlighted. Nanospinel formation from the Al-based quasicrystalline precursor is mentioned.     

Unsteady squeezing flow of water‐based nanofluid between two parallel disks with slip effects: Analytical approach

The squeezing flow of an unsteady water‐based nanofluid between two parallel disks has been analyzed in the current study. Thermal and solutal buoyancy along with heat source enhance the flow phenomena of free convective flow through a porous medium. In addition to that velocity slip and temperature slip are also accounted for in the boundary conditions. The similarity transformation is adopted to formulate the governing equations that convert the complex partial differential equations (PDEs) to nonlinear ordinary differential equations (ODEs). These transformed equations are handled analytically by using the variation parameter method (VPM). For computational purposes, the fixed numeric values of physical parameters are used and their behaviors are shown by means of graphs. The calculated results for the physical quantities of interest are shown in tables. The conformity of the solution is obtained in comparison to an earlier study in a particular case. The major findings are (i) the velocity profile has distinct variations, which are separated by the middle layer of the channel and (ii) enhancement in the heat transfer coefficient is noted due to the interaction of buoyancy parameter.     

Further evaluation of boric acid vis-à-vis other lubricants for cold forming applications

The effectiveness of boric acid as lubricant has been evaluated in ring forging and deep drawing operations. The elapsed lay-by time between boric acid coating preparation and forming operation has significant influence on the friction factor. Fresh surfaces provide least friction since longer lay-by time permits absorption of moisture from the environment and tend to increase friction. Forging speed has no effect on the performance of boric acid lubricant. The average of peak forces obtained with tools having different surface coatings indicated that the hardness of the coating also has no effect on the effectiveness of the boric acid lubricant.     

MapReduce based parallel fuzzy-rough attribute reduction using discernibility matrix

Fuzzy-rough set theory is an efficient method for attribute reduction. It can effectively handle the imprecision and uncertainty of the data in the attribute reduction. Despite its efficacy, current approaches to fuzzy-rough attribute reduction are not efficient for the processing of large data sets due to the requirement of higher space complexities. A limited number of accelerators and parallel/distributed approaches have been proposed for fuzzy-rough attribute reduction in large data sets. However, all of these approaches are dependency measure based methods in which fuzzy similarity matrices are used for performing attribute reduction. Alternative discernibility matrix based attribute reduction methods are found to have less space requirements and more amicable to parallelization in building parallel/distributed algorithms. This paper therefore introduces a fuzzy discernibility matrix-based attribute reduction accelerator (DARA) to accelerate the attribute reduction. DARA is used to build a sequential approach and the corresponding parallel/distributed approach for attribute reduction in large data sets. The proposed approaches are compared to the existing state-of-the-art approaches with a systematic experimental analysis to assess computational efficiency. The experimental study, along with theoretical validation, shows that the proposed approaches are effective and perform better than the current approaches.

     

Random Forest Learning Based Indoor Localization as an IoT Service for Smart Buildings

Wireless Personal Communications - More buildings are becoming smart day by day which play a key role in development of smart cities and Internet of Things is essential in the development of such...     

Performance Analysis for Tri-Gate Junction-Less FET by Employing Trioxide and Rectangular Core Shell (RCS) Architecture

Wireless Personal Communications - With the advancement in technology scaling and featuring new device design is being explored to meet the demand for low power and high-speed circuit design....     

Multi-objective fractional gravitational search algorithm for energy efficient routing in IoT

Wireless Networks - Nowadays, the Internet of Things (IoT) plays a significant role in the Internet world. The IoT is a system which integrates the computing devices, digital machines provided with...     

A novel solution of deep learning for sleep apnea detection: enhancement of SC and elimination of GVICS

Multimedia Tools and Applications - Convolutional neural network (CNN) classification has not achieved a medically-satisfied level of accuracy in sleep apnea detection due to the negative effect of...