Mn0.7Zn0.3Fe2O4 + BaTiO3 composites: structural,morphological, magnetic,M–E effect and dielectric properties

Here in the present investigation, constituent phases of (1 ? x)Mn_0.7Zn_0.3Fe₂O₄(MZFO)?+?(x)BaTiO₃(BTO) (where x?=?0.0, 0.25, 0.50, 0.75 and 1.0) composites have been synthesized by sol–gel auto-ignition route and the composite structure by ceramic route. The XRD analysis ensures that the composite structure consists of both cubic spinel piezomagnetic and perovskite piezoelectric phases. The average crystallite size estimated from Scherrer equation increases from 15.36 to 21.94 nm. The strain induced in individual phases has been investigated by W–H analysis and it is observed that the MZFO phase shows comprehensive type strain while BTO phase shows tensile type strain. Scanning electron micrographs confirm the microstructure of the sample with grain size ranges from 36.006 to 54 nm. Energy dispersive X-ray spectra and elemental color mappings of typical samples (x?=?0.0 and 0.75) clearly indicates the phase purity and stoichiometric proportion of the composites. Fourier transform infrared spectra showed five major absorption bands related to stretching vibrations of different kinds of metal ions and oxygen ions. Increasing percentage of BTO phase in the composite reduces the saturation magnetization, remnant magnetization and coercivity. Real and imaginary parts of permittivity show maximum values at lower frequency region and decrease with increase in applied frequency. For the composition (0.25)MZFO–(0.75)BTO, composite shows maximum value of magnetoelectric coupling coefficient (α_ME?=?20.45 mVcm^?1 Oe^?1). The improved magnetoelectric properties make MZFO–BTO composite applicable for electronic devices.

     

Process Discovery and Refinement of an Enterprise Management System

The need for the analysis of modern businesses is rapidly increasing as the supporting enterprise systems generate more and more data. This data can be extremely valuable for executing organizations because the data allows constant monitoring, analyzing, and improving the underlying processes, which leads to the reduction of cost and the improvement of the quality. Process mining is a useful technique for analyzing enterprise systems by using an event log that contains behaviours. This research focuses on the process discovery and refinement using real-life event log data collected from a large multinational organization that deals with coatings and paints. By investigating and analyzing their order handling processes, this study aims at learning a model that gives insight inspection of the processes and performance analysis. Furthermore, the animation is also performed for the better inspection, diagnostics, and compliance-related questions to specify the system. The configuration of the system and the conformance checking for further enhancement is also addressed in this research. To achieve the objectives, this research uses process mining techniques, i.e. process discovery in the form of formal Petri nets models with the help of process maps, and process refinement through conformance checking and enhancement. Initially, the identified executed process is reconstructed by using the process discovery techniques. Following the reconstruction, we perform a deep analysis for the underlying process to ensure the process improvement and redesigning. Finally, some recommendations are made to improve the enterprise management system processes.     

Correlation Between Texture,Grain Boundary Constitution and Corrosion Behaviour of Copper–Chromium Coatings Containing Graphene Oxide

Metallurgical and Materials Transactions A - Effect of graphene oxide on the corrosion behavior of electrodeposited Cu–Cr coatings on mild steel substrate was studied and the results were...     

A Review on the Effect of Silica to Alumina Ratio,Alkaline Solution to Binder Ratio,Calcium Oxide + Ferric Oxide,Molar Concentration of Sodium Hydroxide and Sodium Silicate to Sodium Hydroxide Ratio on the Compressive Strength of Geopolymer Concrete

Silicon - Recently, geopolymer concrete (GPC) has gained substantial consideration and commercial interest in the construction industry owing to the superior mechanical and chemical properties in...     

Cold plasma treatment advancements in food processing and impact on the physiochemical characteristics of food products

Food Science and Biotechnology - Cold plasma processing is a nonthermal approach that maintains food quality while minimizing the effects of heat on its nutritious qualities. Utilizing activated,...     

L-Shaped Schottky Barrier MOSFET for High Performance Analog and RF Applications

Silicon - This work presents the design and simulation of a novel double-gate L-shaped Schottky barrier MOSFET (DG-LS-SB-MOSFET). The device uses a low work function metal near source-channel...     

Aspect Level Songs Rating Based Upon Reviews in English

With the advancements in internet facilities, people are more inclined towards the use of online services. The service providers shelve their items for e-users. These users post their feedbacks, reviews, ratings, etc. after the use of the item. The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items. Sentiment Analysis (SA) is a technique that performs such decision analysis. This research targets the ranking and rating through sentiment analysis of these reviews, on different aspects. As a case study, Songs are opted to design and test the decision model. Different aspects of songs namely music, lyrics, song, voice and video are picked. For the reason, reviews of 20 songs are scraped from YouTube, pre-processed and formed a dataset. Different machine learning algorithms—Naïve Bayes (NB), Gradient Boost Tree, Logistic Regression LR, K-Nearest Neighbors (KNN) and Artificial Neural Network (ANN) are applied. ANN performed the best with 74.99% accuracy. Results are validated using K-Fold.