Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning.Specifically,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation speed.Diffractive deep neural networks(D²NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D²NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and imaging.Here,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning.After independently training 1252 D²NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D²NNs that collectively improved the image classification accuracy.Through this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D²NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D²NNs within each ensemble.These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.     

Modifications in the properties of gypsum construction element via addition of expanded macroporous silica granules

The present study is focused on the production of light weight silicate based macroporous filler for hardened gypsum and its effect on the product properties. Highly porous, durable foam like silica granules were produced from the relatively low cost material of silica gel desiccant. Swelling behaviour and mineralogical structure of the granules after swelling were examined. Different sample series were produced by replacing gypsum by expanded silica gel. Physical properties of the hardened gypsum were improved by the addition of expanded silica gel granules. Thermal conductivity of the gypsum decreased significantly when the expanded silica gel granules introduced into the gypsum. Expanded silica gel addition also improved the high temperature durability of gypsum. Much better integrity was observed after the testing of samples at 700 °C when compared to control series.     

Electrochemical and thermodynamic studies to evaluate inhibition effect of 2-[(4-phenoxy-phenylimino)methyl]-phenol in 1 M HCl on mild steel

Inhibition of the corrosion of mild steel in 1.0 M HCl solution by a Schiff base compound named 2-[(4-phenoxy-phenylimino)methyl]-phenol (APS) was investigated at different temperatures (25–55 °C) using electrochemical measurements. The inhibition efficiency increased as APS concentration and temperature increased. It was found that adsorption for APS on mild steel complies with the Langmuir adsorption isotherm in all studied temperature. Thermodynamic parameters (ΔG_ads, ΔH_ads and ΔS_ads) for APS adsorption on mild steel were found out and discussed at each temperature. Time dependency of mild steel in 1.0 M HCl solution in the absence and presence of APS was also studied. The surface morphology of mild steel was examined via SEM analysis.     

Electrospun polymeric nanofibrous composites containing TiO2 short nanofibers

In this study, polymeric nanofibrous composites containing anatase TiO₂ short nanofibers (TiO₂-SNF) were successfully produced via electrospinning. The fabrication of the nanofibrous composite structure includes two steps. First, anatase TiO₂ nanofibers were obtained by calcination of electrospun PVP/TiO₂ nanofibers and then crushed into short nanofibers ranging from few microns in length. Second, these TiO₂-SNF were dispersed into polymer solutions and then electrospun into nanofibrous composites. We obtained nanofibers containing TiO₂-SNF from different polymer types including PMMA, PAN, PET and PC. The SEM and TEM imaging indicated that some of the TiO₂-SNF were fully covered by the polymeric matrix whereas some TiO₂-SNF were partially covered and/or stick on the surface of the fibers. The photocatalytic activity of nanofibrous composites containing TiO₂-SNF was evaluated by monitoring the photocatalytic decomposition of a model dye (rhodamine-6G) under UV irradiation.     

Diffusion bonding of electroless Ni plated WC composite to Cu and AISI 316 stainless steel

In this study, a composite containing WC (Tungsten Carbide) and Ni was produced by two different processing routes. Electroless Ni coated WC powders were consolidated and sintered at 1200 °C. Diffusion bonding couples of WC(Ni)-electrolytic Cu, WC(Ni)-AISI 316 stainless steel and WC(Ni)-WC(Ni) were manufactured by using a preloaded compression system under Ar atmosphere. Diffusion bonding was carried out at varying bonding temperatures; 750 °C for (WC)Ni-Cu diffusion couple and 1200 °C for (WC)Ni-(WC)Ni and (WC)Ni-AISI 316 stainless steel diffusion couples. Standard metallographic techniques, Scanning Electron Microscopy and a shear test were employed to characterize the microstructure of bondline and mechanical properties of each diffusion couple, respectively.     

A new size distribution model by t-family curves for comminution of limestones in an impact crusher

In the evaluation of crushers, t-family curves obtained from single particle test methods are frequently used. It is known that there are many difficulties and problems in these tests. In this study the breakage behaviour of three different limestones in an impact crusher was investigated. A new size distribution model was developed by t-family value evaluation and Bond work index approach. As a result, the validity of the equation was proved by a high regression value (r² = 0.88).     

Effect of Boron and Heat Treatment on Mechanical Properties of White Cast Iron for Mining Application

 Heat treatment methods were applied to white cast iron for improving the impact and wear resistance. Additionally, chemical composition optimization was made. Furthermore, the effect of boron addition on such applications was investigated. Samples were investigated by using optical and electron microscope methods. Hardness, wear and impact tests were conducted. The results showed that the secondary carbides in the standard alloy were iron-enriched, needle-like carbides M3C when the boron-added alloy contained Fe23(C,B)6 type, globular secondary carbides. It was concluded that heat treatment B provided higher wear and hardness properties, compared to the standard heat treatment. Optimum mechanical properties were obtained by lower destabilisation temperatures and increasing temperature reduced the wear resistance and hardness.     

Analysis and compensation of mass loading effect of accelerometers on tool point FRF measurements for chatter stability predictions

Chatter is one of the major problems in machining resulting in poor surface quality and reduced productivity. Stability diagrams can be used to determine chatter-free process conditions yielding high productivity. For generation of stability diagrams, frequency response functions (FRF) at the tool tip are needed to be used in stability models. Impact tests involving accelerometers are commonly used in FRF measurements. Although mass of a typical accelerometer used in these measurements is extremely small compared with the cutting tool, it can have a significant effect on the FRF measurement. In this paper, the effect of accelerometer’s mass on tool point FRFs and stability diagrams is demonstrated for several cases with different tool-to-accelerometer mass ratios by using laser velocity sensor measurements. In addition, a structural modification method which can be used to compensate this effect is also presented on several cases. The structural modification method can be used to correct the FRFs measured with accelerometers, and thus the resulting stability diagrams.     

The effect of alcohol on the passivation of al alloys in 1 N H<Subscript>2</Subscript>SO<Subscript>4</Subscript> solution

In this study, the influence of different alcohol on the passivation of aluminium alloys have been investigated by using current-potential curves. Experimental results show that the addition of alcohol in H₂SO₄ solution have been changed passivation potential distance of the alloys. Elemental compositions of alloys have also directly affected passivation of alloys. This influence is more effective especially in alloys content higher Si also and less Cu.