There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

CNN-DMRI: A Convolutional Neural Network for Denoising of Magnetic Resonance Images

Medical Imaging is the most significant technique that constitutes information needed to diagnose and make the right decisions for treatment. These images suffer from inadequate contrast and noise that occurs during image acquisition. Thus, denoising and contrast enhancement is crucial in increasing the visual quality of the images for obtaining quantitative measures. In this research, an innovative and improvised denoising technique is implemented that applies a sparse aware with convolution neural network (SA_CNN) for investigating various medical modalities. To evaluate and validate, the convolution neural network utilizes patch creation and dictionary methods for obtaining information. The proposed framework is predominant to other current approaches by employing image assessment quantitative measures like peak signal to noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). The study also optimizes the computational time to achieve increased efficiency and better visual quality of the image. Furthermore, the widespread use of the Internet of Healthcare Things (IoHT) helps to provide security with vault and challenge schemes between IoT devices and servers.

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Security Assured CNN-Based Model for Reconstruction of Medical Images on the Internet of Healthcare Things

Strain hardening behavior and microstructural evolution of non-grain oriented electrical, dual phase, and AISI 304 steels, subjected to uniaxial tensile tests, were investigated in this study. Tensile tests were performed at room temperature and the strain hardening behavior of the steels was characterized by three different parameters: modified Crussard–Jaoul stages, strain hardening rate and instantaneous strain hardening exponent. Optical microscopic analysis, X-ray diffraction measurements, phase quantification by Rietveld refinement and hardness tests were also carried out in order to correlate the microstructural and mechanical responses to plastic deformation. Distinct strain hardening stages were observed in the steels in terms of the instantaneous strain hardening exponent and the strain hardening rate. The dual phase and non-grain oriented steels exhibited a two-stage strain hardening behavior while the AISI 304 steel displayed multiple stages, resulting in a more complex strain hardening behavior. The dual phase steels showed a high work hardening capacity in stage 1, which was gradually reduced in stage 2. On the other hand, the AISI 304 steel showed high strain hardening capacity, which continued to increase up to the tensile strength. This is a consequence of its additional strain hardening mechanism, based on a strain-induced martensitic transformation, as shown by the X-ray diffraction and optical microscopic analyses.

Strain hardening behavior and microstructural evolution during plastic deformation of dual phase, non-grain oriented electrical and AISI 304 steels

Local activity-driven structural-preserving filtering for noise removal and image smoothing

NLM based magnetic resonance image denoising – A review

1) Department of Metallurgical and Materials Engineering, Visvesvaraya National Institute of Technology, South Ambazari Road, Nagpur – 440010 India. E-mail: rajesh.khatirkar@gmail.com 2) Department of Metallurgical Engineering and Materials Science, IIT Bombay, Powai, Mumbai – 400076 India. E-mail: vbasavaraj@iitb.ac.in, indra@iitb.ac.in 3) RD & T, Tata Steel Europe, Swinden Technology Centre, Rotherham, S60 3AR UK. E-mail: arunansuhaldar@gmail.com

ND// Recrystallization in Interstitial Free Steel : The Defining Role of Growth Inhibition

In the present investigation, ER2594 (conventional) and ER2595 (consisting of additional Cu and W) electrodes were used to produce butt joints of 5.5 mm thick super duplex stainless steel (UNS S32750) sheets using shielded metal arc welding (SMAW) process. During SMAW process, the heat input was 0.81 kJ mm−1 for ER2594 electrode and 0.75 kJ mm−1 for ER2595 electrode. Optical microscope and scanning electron microscope were used to observe the microstructures of different zones, namely, fusion zone (FZ), heat affected zone (HAZ) and base metal (BM). Tensile test, impact test and micro-hardness measurements were carried out for both the weldments on samples cut across the weld. The microstructures of the FZ consisted of inter-granular austenite (IGA), grain boundary austenite (GBA) and Widmanstatten austenite (WA). There was minor change in the width of the HAZ of the weldments with the change in electrode. This is expected to be due to the minor change in the heat input during SMAW process. The weld zone (cap pass) of both the weldments predominantly showed WA and mode of solidification was found to be ferritic (F mode). The tensile strength of both the weldments was approximately same as that of base metal and both the samples fractured through the BM. Cr, Fe and Mo rich precipitates were found in the FZ (weld region), which are expected to be formed due to pick of gaseous content from the atmosphere during welding. The FZ of the weldments produced by ER2595 electrode showed better pitting corrosion resistance than those produced by ER2594 electrode.

Shielded metal arc welding of UNS S32750 steel: microstructure, mechanical properties and corrosion behaviour

Orientation Dependent Recovery in Interstitial Free Steel

Experimental forming limit curves (FLCs) were determined for two different grades of low-carbon steel: interstitial free (IF) and drawing quality (DQ). The grades had different interstitial content, clear differences in microstructural evolution, and differences in experimental FLCs. Microstructural evolution was generalized in terms of developments in crystallographic texture and in-grain misorientations. These were extrapolated further into dynamic values of normal anisotropy (
 $$ \overline{r} $$
 ) and strain hardening exponent (n), respectively. FLCs were simulated by finite element (FE) analysis. Simulations were conducted using constant (or initial) and dynamic material properties (namely, $$ \overline{r} $$
 and n). Simulations using the dynamic variation in the material properties showed better comparison to the experimental FLCs.

Basavaraj H. Vadavadagi

Papers

NLM based magnetic resonance image denoising – A review

ND// Recrystallization in Interstitial Free Steel : The Defining Role of Growth Inhibition

Shielded metal arc welding of UNS S32750 steel: microstructure, mechanical properties and corrosion behaviour

Orientation Dependent Recovery in Interstitial Free Steel

Forming limit curves in low-carbon steels: improved prediction by incorporating microstructural evolution