Lateral Magnetically Modulated Multilayers by Combining Ion Implantation and Lithography

The combination of lithography and ion implantation is demonstrated to be a suitable method to prepare lateral multilayers. A laterally, compositionally, and magnetically modulated microscale pattern consisting of alternating Co (1.6 µm wide) and Co‐CoO (2.4 µm wide) lines has been obtained by oxygen ion implantation into a lithographically masked Au‐sandwiched Co thin film. Magnetoresistance along the lines (i.e., current and applied magnetic field are parallel to the lines) reveals an effective positive giant magnetoresistance (GMR) behavior at room temperature. Conversely, anisotropic magnetoresistance and GMR contributions are distinguished at low temperature (i.e., 10 K) since the O‐implanted areas become exchange coupled. This planar GMR is principally ascribed to the spatial modulation of coercivity in a spring‐magnet‐type configuration, which results in 180° Néel extrinsic domain walls at the Co/Co‐CoO interfaces. The versatility, in terms of pattern size, morphology, and composition adjustment, of this method offers a unique route to fabricate planar systems for, among others, spintronic research and applications.     

Performance Analysis of Novel Multi-band Monopole Antenna for Various Broadband Wireless Applications

Wireless Personal Communications - This study investigates a novel concept of using slot and Coplanar Waveguide fed antenna to obtain multiband operation. The compact antenna includes a star...     

Tobit model analysis of mutations causing haemophilia

Haemophilia A is a genetic disease resulting from deficiency of factor VIII. The database of mutations causing haemophilia A has been developed by the worldwide collaboration. In this study, we predicted the severity of haemophilia A using ordinary least squares regression (OLS) and Tobit model regression in factor VIII. As parameters, we used four physical–chemical parameters of amino acids and the accessible surface area. As the result, there is a difference between OLS and Tobit model analysis in the prediction of haemophilia A severity. We found that the predicted value by Tobit model in severe data is close to the observed value. These results suggest that Tobit model regression analysis is superior to estimating severity of haemophilia A in severe data than OLS.     

Improved iterative joint detection and estimation through variational Bayesian inference

We propose an improved variational Bayesian (VB) receiver for orthogonal frequency-division multiplexing (OFDM) systems over frequency-selective block-fading channels. Conventional VB receivers provide distribution-estimates for the channel and information symbols iteratively and jointly. The proposed scheme is different from conventional VB inference in that the VB iterative receiver also exploits the hard channel estimate extracted from previous iterations to update the channel and symbol distributions. In this way, we reduce the impact of channel uncertainty on the decoder performance by means of a modified formulation of the VB formalism. The adequacy of the proposed approach compared to classically used VB receivers is demonstrated by simulations.     

Performance comparison of deep learning architectures for surgical instrument image removal in gastrointestinal endoscopic imaging

Artificial Life and Robotics - Endoscopic images typically contain several artifacts. The artifacts significantly impact image analysis result in computer-aided diagnosis. Convolutional neural...     

Design of CO2 absorption plant for recovery of CO2 from flue gases of gas turbine

The ongoing human-induced emission of carbon dioxide (CO₂) threatens to change the earth's climate. A major factor in global warming is CO₂ emission from thermal power plants, which burn fossil fuels. One possible way of decreasing CO₂ emissions is to apply CO₂ removal, which involves recovering of CO₂ from energy conversion processes. This study is focused on recovery of CO₂ from gas turbine exhaust of Sarkhun gas refinery power station. The purpose of this study is to recover the CO₂ with minimum energy requirement. Many of CO₂ recovery processes from flue gases have been studied. Among all CO₂ recovery processes which were studied, absorption process was selected as the optimum one, due to low CO₂ concentration in flue gas. The design parameters considered in this regard, are: selection of suitable solvent, solvent concentration, solvent circulation rate, reboiler and condenser duty and number of stages in absorber and stripper columns. In the design of this unit, amine solvent such as, diethanolamine (DEA), diglycolamine (DGA), methyldiethanolamine (MDEA), and monoethanolamine (MEA) were considered and the effect of main parameters on the absorption and stripping columns is presented. Some results with simultaneous changing of the design variables have been obtained. The results show that DGA is the best solvent with minimum energy requirement for recovery of CO₂ from flue gases at atmospheric pressure.     

Validity of decision mode analysis on an ROI determination problem in multichannel fNIRS data

Region of interest (ROI) determination is necessary when using functional near-infrared spectroscopy (fNIRS) data to detect brain activity. To extract ROIs from multiple fNIRS channels, we investigated the validity of applying decision mode analysis to the fNIRS dataset. This classifies a dataset into clusters with similar features. For each cluster, the dataset is decomposed into a mean vector and a linear combination of eigenvectors. Applying this to fNIRS signals, the mean vector can be used to represent change in hemoglobin (Hb), and the eigenvectors interpreted as a signal component constructing the arbitrary signal. Characterizing these vectors by correlating them with a theoretical model of brain function aids our understanding of where Hb changes occur and what type of Hb changes reflect brain activity in fNIRS data. Decision mode analysis of fNIRS data measured during viewing stereoscopic images identified ROIs around the right inferior frontal gyrus associated with attentional control, and frontal association area associated with decision on action and prediction. Our experimental results showed that information obtained from decision mode analysis can aid quantitative and qualitative ROI determination.     

Effect of Temperature on Young's Modulus of Graphene

The temperature dependence of the thermo-mechanical behavior of materials is of great importance in many engineering applications where the precise properties of materials over an extended temperature range are needed. The objective of this work is to present a density functional study to predict the temperature variation of Young's modulus of graphene. To this end, the energies of phonons as well as thermodynamic functions are calculated from phonon calculations via the quasi-harmonic approximation. It is observed that with the increase of strain the phonon energy decreases. Also, by increasing temperature up to a special value which is around 400 K, Young's modulus decreases appreciably. For the temperatures higher than 400 K, Young's modulus decreases with a lower rate and tends to be constant at high temperatures. The results obtained are in a good agreement with the experimental data previously reported in the literature.