Physico-chemical characteristics of high performance polymer modified by low and atmospheric pressure plasma

In this work, the effect of low pressure plasma and atmospheric-pressure plasma treatment on surface properties and adhesion characteristics of high performance polymer, Polyether Ether Ketone (PEEK) are investigated in terms of Fourier Transform Infrared Spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and Atomic Force Microscopy (AFM). The experimental results show that the PEEK surface treated by atmospheric pressure plasma lead to an increase in the polar component of the surface energy, resulting in improving the adhesion characteristics of the PEEK/Epoxy adhesive system. Also, the roughness of the treated surfaces is largely increased as confirmed by AFM observation. These results can be explained by the fact that the atmospheric pressure plasma treatment of PEEK surface yields several oxygen functionalities on hydrophobic surface, which play an important role in increasing the surface polarity, wettability, and the adhesion characteristics of the PEEK/Epoxy adhesive system.     

An International Collaborative Study on Trypsin Inhibitor Assay for Legumes,Cereals, and Related Products

For determining trypsin inhibitor activity (TIA) in soy products, the American Oil Chemists' Society (AOCS) Method Ba 12-75 has been used. It measures differences in absorbance at 410 nm of bovine trypsin activity toward a synthetic substrate (Nα-benzoyl-DL-arginine-p-nitroanilide) in the absence and presence of an inhibitor. Recently, a significantly improved method was developed (JAOCS, 2019, 96:635–645), featuring 5 mL of total assay volume, enzyme-last sequence, and single inhibitor level in duplicate. It is proposed as the AOCS Method Ba 12a-2020. As a part of the AOCS method approval process, a collaborative study involving 12 international laboratories was conducted to evaluate the performance of the proposed method. The study involved measuring TIA in 10 selected test samples plus a blind duplicate. They included soybeans, pulses, cereals, and their processed products (flours, concentrates, and isolates). After rigorous statistical treatment of the data, only three outliers were removed from the data of two samples. Repeatability relative standard deviations (RSDr) for the 11 samples ranged from 0.99% to 5.52%. Reproducibility RSD (RSD_R) ranged from 7.07% to 22.92%, with seven samples having RSD_R around 10% or less. The remaining four samples had very low TIA, and their RSD_R values ranged from 13.34% to 22.92%. The study has demonstrated reliable performance of the proposed AOCS method. Several collaborators carried out additional experiments addressing some aspects of the method, leading to further refinements. The proposed method is undergoing evaluation by the AOCS Uniform Methods Committee for adoption as an Official Method for measuring TIA in various legume and grain products.     

Sensorless current control for active rectifiers

A novel model-based sensorless-input current controller for three-phase active rectifiers is presented. The proposed algorithm is based upon a load-conductance rectifier controller, which was previously implemented using current sensors. The paper presents analytical studies and simulation results and discusses a simple implementation using a low cost integrated microcontroller. Experimental verification utilizes an active input/output insulated gate bipolar transistor (IGBT) converter. Simulation and experimental results for the proposed controller are compared to that of the sensor-based version to validate the efficacy of this novel algorithm     

A novel wavelet transform aided neural network based transmission line fault analysis method

In the present scenario of market driven business, power supply has become more like a commodity. Reliable and quality power need to be ensured to meet customer requirements. In such a situation, it is extremely important that transmission line faults be identified accurately, reliably and in quick time. Advanced signal processing tools such as discrete wavelet transform (DWT) can be used very effectively for parameterisation and characterization of the fault signals. On the other hand, properly configured neural network (NN) can be utilized for classification of the faults based on the DWT signal. The present contribution uses electromagnetic transient program (EMTP) for modeling of a real transmission system and MATLAB for DWT and NN. Various types of faults have been simulated at different locations along the transmission line and an attempt has been made to correctly identify and locate the fault.     

A New Method for Getting Rational Approximation for Fractional Order Differintegrals

In this paper a new algorithm is presented to calculate the poles and zeros to approximate a fractional order (FO) differintegral (s^±α,α∈(0,1)) by a rational function on a finite frequency band ω∈(ω_l,ω_h). The constant phase property of the FO differintegral is the basis for development of the algorithm. Interlacing of real poles and zeros is used to achieve the constant phase. The calculations are done using the asymptotic Bode phase plot. A brief investigation is made to get a good approximation for the Bode phase plot. Two design parameters are introduced to keep the average phase close to the desired phase angle and to keep the error within the allowed bounds. A study is done to empirically understand the relationship between the error and the design parameters. The results thus obtained help in the further calculations. The algorithm is computationally simple and inexpensive, and gives a fairly good approximation of fractance frequency response on the specified frequency band.     

3D computer vision based on machine learning with deep neural networks: A review

Recent advances in the field of computer vision can be attributed to the emergence of deep learning techniques, in particular convolutional neural networks. Neural networks, partially inspired by the brain's visual cortex, enable a computer to “learn” the most important features of the images it is shown in relation to a specific, specified task. Given sufficient data and time, (deep) convolutional neural networks offer more easily designed, more generalizable, and significantly more accurate end‐to‐end systems than is possible with previously employed computer vision techniques. This review paper seeks to provide an overview of deep learning in the field of computer vision with an emphasis on recent progress in tasks involving 3D visual data. Through a backdrop of the mammalian visual processing system, we hope to also provide inspiration for future advances in automated visual processing.     

Text and non-text separation in offline document images: a survey

International Journal on Document Analysis and Recognition (IJDAR) - Separation of text and non-text is an essential processing step for any document analysis system. Therefore, it is important to...     

A novel microfluidic switch for pH control using Chitosan based hydrogels

We report a novel pH-sensitive hydrogel based micro-valve for metered flow that has applications in a laboratory made “Intelligent valving system”. The hydrogel solution was prepared through Chitosan and poly vinyl alcohol in acetic acid and crystallized using gluteraldehyde as the crosslinking agent in the form of thin wafers and it was found to be very sensitive to pH changes. The pore structure of hydrogel was investigated through Field Emission Scanning Electron Microscopy and thin wafers of the gel were physically placed inside PDMS microchannels. Flow metering in these channels was observed by controlled expansion of the hydrogel plug till complete valving was realized. This valving device was further precisely characterized with micro Particle Image Velocimetry using a solution containing fluorescent polymeric micro beads. The principle advantage of this hydrogel device is the smaller range of pH (varying between pH 3 and 7) over which the valving response is observed.