Evapotranspiration Modeling Using Different Tree Based Ensembled Machine Learning Algorithm

Water Resources Management - The present study investigates and evaluate the scope and potential of modern computing tools and techniques such as ensembled machine learning methods in estimating...     

Tuning of shear thickening behavior and elastic strength of polyvinylidene fluoride via doping of ZnO-graphene

ZnO rice like nonarchitects are grafted on the graphene carbon core via a rapid microwave synthesis route. The prepared grafted systems are characterized via XRD, SEM, RAMAN, and XPS to examined the structural and morphological parameters. Zinc oxide grafted graphene sheets (ZnO-G) are further doped in β-phase of polyvinylidene fluoride (PVDF) to prepare the polymer nanocomposites (PNCs) via mixed solvent approach (THF/DMF). β-phase confirmation of PVDF PNCs is done by FTIR studies. It is observed that ZnO-G filler enhances the β-phase content in the PNCs. Non-doped PVDF and PNCs are further studied for rheological behavior under the shear rate of 1–100 s⁻¹. Doping of ZnO-G dopant to the PVDF matrix changes its discontinuous shear thickening (DST) behavior to continues shear thickening behavior (CST). Hydrocluster formation and their interaction with the dopant could be the reason for this striking DST to CST behavioral change. Strain amplitude sweep (10⁻³% -10%) oscillatory test reveals that the PNCs shows extended linear viscoelastic region with high elastic modulus and lower viscous modulus. Effective shear thickening behavior and strong elastic strength of these PNCs present their candidature for various fields including mechanical and soft body armor applications.     

Process Variation Study of SELBOX Inverted- T Junctionless FinFET for High-Performance Applications

This work investigates the performance of the inverted-T (IT) junctionless (JL) FinFET with selective buried oxide (SELBOX) topology. The electrical charac     

A novel binary gaining–sharing knowledge-based optimization algorithm for feature selection

Neural Computing and Applications - To obtain the optimal set of features in feature selection problems is the most challenging and prominent problem in machine learning. Very few human-related...     

PRATIT: a CNN-based emotion recognition system using histogram equalization and data augmentation

Multimedia Tools and Applications - Emotions are spontaneous feelings that are accompanied by fluctuations in facial muscles, which leads to facial expressions. Categorization of these facial...     

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.     

Why does it pay to be selfish in a MANET?

Routing protocols for a mobile ad hoc network have assumed that all mobile nodes voluntarily participate in forwarding others' packets. This was a reasonable assumption because all MNs in a MANET belonged to a single authority. In the near future, however, a MANET may consist of MNs that belong to many different organizations since numerous civilian applications are expected to crop up. In this situation, some MNs may run independently and purposely decide not to forward packets so as to save their own energy. This could potentially lead to network partitioning and corresponding performance degradation. To minimize such situations in MANETs, many studies have explored the use of both the carrot and the stick approaches by having reputation-based, credit-payment, and game theory schemes. This article summarizes existing schemes, identifies their relative advantages, and projects future directions     

The relationship between bioelectrical impedance phase angle and subjective global assessment in advanced colorectal cancer

Background  

Bioelectrical Impedance (BIA) derived phase angle is increasingly being used as an objective indicator of nutritional status in advanced cancer. Subjective Global Assessment (SGA) is a subjective method of nutritional status. The objective of this study was to investigate the association between BIA derived phase angle and SGA in advanced colorectal cancer.