The applicability of neural networks in the determination of soil profiles

The drilling of a number of boreholes to determine the soil profile of a given area is time consuming and costly. This paper describes estimated soil profiles obtained using a model based on artificial neural networks (ANN). ANN is a powerful data-modelling tool capable of capturing and representing complex relationships between input and output. It deals with many multi-variate problems for which an exact analytical model does not exist or is very difficult and time consuming to develop. The main settlement in the Adapazari region was selected to demonstrate the capability of such model. The results obtained using ANN are promising when compared with the soil profile obtained from boreholes.      

Adaptive-Network-Based Fuzzy Inference System Analysis to Predict the Temperature and Flow Fields in a Lid-Driven Cavity

Heat transfer behavior in a 2-D square lid-driven cavity has been studied for various pertinent Reynolds and Rayleigh numbers. The lattice Boltzmann method, a numerical tool based on the particle distribution function is applied to simulate a thermal fluid flow problem. Bhatnagar-Gross-Krook (BGK) is combined with the double population thermal Lattice Boltzmann model to solve mixed convection in a square cavity. An adaptive-network-based fuzzy inference system (ANFIS) method is trained and validated using BGK Lattice Boltzmann model results. The results show that the trained ANFIS model successfully predicts the temperature and flow fields in a few seconds with acceptable accuracy.     

Multiferroic behavior of the functionalized surface of a flexible substrate by deposition of Bi2O3 and Fe2O3

Thin films of bismuth and iron oxides were obtained by atomic layer deposition (ALD) on the surface of a flexible substrate poly(4,4′-oxydiphenylene-pyromellitimide) (Kapton) at a temperature of 250°C. The layer thickness was 50 nm. The samples were examined by secondary-ion mass spectrometry, and uniform distribution of elements in the film layer was observed. Surface morphology, electrical polarization, and mechanical properties were investigated by atomic force microscope, piezoelectric force microscopy, and force modulation microscopy. The values of current in the near-surface layer varied in the range of ±80 pA when a potential of 5 V was applied. Chemical analysis was performed by X-ray photoelectron spectroscopy, where the formation of Bi₂O₃ and Fe₂O₃ phases, as well as intermediate phases in the Bi–Fe–O system, was observed. Magnetic measurements were carried out by a vibrating sample magnetometer that showed a ferromagnetic response. The low-temperature method of functionalization of the Kapton surface with bismuth and iron oxides will make it possible to adapt the Bi–Fe–O system to flexible electronics.     

Structural,Dielectric, and Magnetic Properties of Ba-Doped Multiferroic Bismuth Ferrite

The main focus of the research was to correlate the microstructure with dielectric and magnetic properties of Bi1-xBaxFeO3 samples. Bi1-xBaxFeO3 samples(x = 0.1, 0.2 and 0.3) were synthesized by the conventional solid-state reaction method using nano-powders of Bi2O3, Fe2O3, and BaCO3. Thereafter, field emission scanning electron microscope and X-ray diffraction(XRD) techniques were used to examine the structure and phase of the samples. Phase analysis by XRD indicated that the single-phase perovskite structure was formed with possible increment in lattice parameter with increasing Ba doping. Complex permeability(u'iand u'i) measured using impedance analyzer confirmed the increase in magnetic property with increasing Ba doping. Finally, dielectric constant(k) was analyzed as a function of temperature at different frequencies. Dielectric constant as high as 2900 was attained in this research for Bi0.8Ba0.2FeO3 sample due to reduction in leakage current at this composition.     

Hydrogen production via propane dry reforming: Carbon deposition and reaction-deactivation study

Carbon deposition during carbon dioxide reforming reaction of C₃H₈ has been studied over alumina-supported bimetallic Mo/CoNi catalysts. To better understand the carbon-induced deactivation during the reforming reaction, changes in catalyst morphology and carbon deposition kinetics were examined. Different characterization techniques were used for both fresh and rejuvenated catalysts including liquid nitrogen adsorption/desorption, chemisorption via hydrogen, ammonia and CO₂ desorption, and thermogravimetric measurement of the coked catalysts. The time dependant reaction rate profiles indicated that MoNi catalyst has higher syngas (H₂/CO) formation rates with lower CO₂ rate of consumption compared to CoNi catalyst. However, the H₂:CO ratio values were almost the same for both catalysts suggesting similarity in the product formation pathway. Conversion-time analysis showed that MoNi catalyst was more stable and active during a 72-h run while CoNi suffered noticeable deactivation after 30 h on-stream. Reaction-deactivation models implicated a higher deactivation coefficient (k_d) with activation energy of E_d = 78.1 kJ mol^?1 for the cobalt-containing Ni catalyst, while the Ni catalyst with molybdenum had a lower deactivation coefficient with smaller activation energy of just under 70 kJ mol^?1. Post-mortem analysis (TPR-TPO dual cycle and TOC) of spent catalysts confirmed that the surface of CoNi catalyst has more carbon residue than the MoNi sample which was consistent with the higher deactivation of CoNi.     

Statistical Analysis and Multimodal Classification on Noisy Eye Tracker and Application Log Data of Children with Autism and ADHD

Emotion recognition behavior and performance may vary between people with major neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and control groups. It is crucial to identify these differences for early diagnosis and individual treatment purposes. This study represents a methodology by using statistical data analysis and machine learning to provide help to psychiatrists and therapists on the diagnosis and individualized treatment of participants with ASD and ADHD. In this paper we propose an emotion recognition experiment environment and collect eye tracker fixation data together with the application log data (APL). In order to detect the diagnosis of the participant we used classification algorithms with the Tomek links noise removing method. The highest classification accuracy results were reported as 86.36% for ASD vs. Control, 81.82% for ADHD vs. Control and 70.83% for ASD vs. ADHD. This study provides evidence that fixation and APL data have distinguishing features for the diagnosis of ASD and ADHD.     

Viscous dissipation effects on thermal transport characteristics of combined pressure and electroosmotically driven flow in microchannels

This study investigates the influence of viscous dissipation on thermal transport characteristics of the fully developed combined pressure and electroosmotically driven flow in parallel plate microchannels subject to uniform wall heat flux. Closed form expressions are obtained for the transverse distributions of electrical potential, velocity and temperature and also for Nusselt number. From the results it is realized that the Brinkman number has a significant effect on Nusselt number. Generally speaking, to increase Brinkman number is to decrease Nusselt number. Although the magnitude of Joule heating can affect Brinkman number dependency of Nusselt number, however the general trend remains unchanged. Depending on the value of flow parameters, a singularity may occur in Nusselt number values even in the absence of viscous heating, especially at great values of dimensionless Joule heating term. For a given value of Brinkman number, as dimensionless Debye–Huckel parameter increases, the effect of viscous heating increases. In this condition, as dimensionless Debye–Huckel parameter goes to infinity, the Nusselt number approaches zero, regardless of the magnitude of Joule heating. Furthermore, it is realized that the effect of Brinkman number on Nusselt number for pressure opposed flow is more notable than purely electroosmotic flow, while the opposite is true for pressure assisted flow.     

Accurate event-driven motion compensation in high-resolution PET incorporating scattered and random events

With continuing improvements in spatial resolution of positron emission tomography (PET) scanners, small patient movements during PET imaging become a significant source of resolution degradation. This work develops and investigates a comprehensive formalism for accurate motion-compensated reconstruction which at the same time is very feasible in the context of high-resolution PET. In particular, this paper proposes an effective method to incorporate presence of scattered and random coincidences in the context of motion (which is similarly applicable to various other motion correction schemes). The overall reconstruction framework takes into consideration missing projection data which are not detected due to motion, and additionally, incorporates information from all detected events, including those which fall outside the field-of-view following motion correction. The proposed approach has been extensively validated using phantom experiments as well as realistic simulations of a new mathematical brain phantom developed in this work, and the results for a dynamic patient study are also presented.      

An Investigation into the Corrosion Behavior of MgO/ZrO<Subscript>2</Subscript> Nanocomposite Coatings Prepared by Plasma Electrolytic Oxidation on the AZ91 Magnesium Alloy

Plasma electrolytic oxidation (PEO) of AZ91 Mg alloys was performed in ZrO₂ nanoparticles containing Na₂SiO₃-based electrolytes. The phase composition and the microstructure of PEO coatings were analyzed by x-ray diffraction and scanning electron microscopy followed by energy dispersive spectroscopy. Pitting corrosion properties of the coatings were investigated using cyclic polarization and electrochemical impedance spectroscopy tests in a Ringer solution. The results showed the better pitting corrosion resistance of the composite coating, as compared to the oxide one, due to the thickened inner layer and the decrease in the surface defects of the composite coating. Also, the PEO process decreased the corrosion current density from 25.06 µA/cm² in the Mg alloy to 2.7 µA/cm² in the oxide coating and 0.47 µA/cm² in the composite coating.