Modeling of the Magnetization and Magnetocaloric Effect in Ni2MnGa Heusler Alloy with the Effective Field Theory

Journal of Low Temperature Physics - This study modeled and investigated the magnetocaloric effect in Ni2MnGa Heusler alloy characterized by its magnetic entropy change (ΔSm) and its...     

Ultra-compact with improved data rate optical encoder based on 2D linear photonic crystal ring resonator

Photonic Network Communications - In the present work, a high-speed optical encoder is proposed based on two-dimensional photonic crystal ring resonator using coupled mode theory and resonance...     

Archetypes of open-source business models

Electronic Markets - The open-source paradigm offers a plethora of opportunities for innovative business models (BMs) as the underlying codebase of the technology is accessible and extendable by...     

Nonsimilar solution of a boundary layer flow of a Reiner–Philippoff fluid with nonlinear thermal convection

The thermodynamics modeling of a Reiner–Philippoff-type fluid is essential because it is a complex fluid with three distinct probable modifications. This fluid model can be modified to describe a shear-thinning, Newtonian, or shear-thickening fluid under varied viscoelastic conditions. This study constructs a mathematical model that describes a boundary layer flow of a Reiner–Philippoff fluid with nonlinear radiative heat flux and temperature- and concentration-induced buoyancy force. The dynamical model follows the usual conservation laws and is reduced through a nonsimilar group of transformations. The resulting equations are solved using a spectral-based local linearization method, and the accuracy of the numerical results is validated through the grid dependence and convergence tests. Detailed analyses of the effects of specific thermophysical parameters are presented through tables and graphs. The study reveals, among other results, that the buoyancy force, solute and thermal expansion coefficients, and thermal radiation increase the overall wall drag, heat, and mass fluxes. Furthermore, the study shows that amplifying the space and temperature-dependent heat source parameters allows fluid particles to lose their cohesive force and, consequently, maximize flow and heat transfer.     

An Efficient Near Lossless Image Compression Algorithm Using Dissemination of Spatial Correlation for Remote Sensing Color Images

Wireless Personal Communications - Image transmission from space borne equipment is a challenging task owing to its restrictions on bandwidth and memory requirement. Many of the state of art...     

Mobile data offloading based on minority game theoretic framework

Wireless Networks - Mobile data offloading is a current-day networking paradigm to channelize certain fraction of the cellular data traffic over unlicensed spectrum of WiFi. In this paper, we...     

GaN Quantum-Dot Formation by a Temperature Increase in an Ammonia Flow

Semiconductors - The transformation of a two-dimensional GaN layer into three-dimensional islands (2D–3D transition) under increasing temperature in a flow of ammonia is investigated...     

Assessment of technological attributes of autochthonous starter cultures in Turkish dry fermented sausage (sucuk)

The study aims to evaluate the technological properties of autochthonous strains (Lactobacillus sakei S15, Lactobacillus plantarum S24, L. plantarum S91, Pediococcus pentosaceus S128b and Staphylococcus carnosus G109) in Turkish dry fermented sausage (sucuk). After 24 h of fermentaPtion, all lactic acid bacteria strains reduced the pH to below 5.0, while the pH in the control group was above 5.3. The number of lactic acid bacteria strains reached 10⁸–10⁹ cfu g⁻¹ during fermentation. Staphylococcus carnosus G109 remained at the inoculation level of 10⁶ cfu g⁻¹ during ripening. Lactobacillus sakei S15 as mono-culture showed higher TBARS values compared to other strains. The control group had the lowest L* value and autochthonous strains caused no significant difference for a* value. According to principal component analysis results, most volatile compounds were positively correlated with the group containing only L. sakei S15.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.