Ghulam Ishaq Khan Institute of Engineering Sciences and Technology

About: Ghulam Ishaq Khan Institute of Engineering Sciences and Technology is a education organization based out in Topi, Pakistan. It is known for research contribution in the topics: Thin film & Quantum efficiency. The organization has 618 authors who have published 940 publications receiving 10674 citations.

Stack-run adaptive wavelet image coding

Abstract: Summary form only given. An adaptive wavelet transform based on an image coder that employs a stack-run representation for quantized transform coefficients and benefits from the intra-subband redundancies is presented. The compression algorithm can be divided into four parts. First, an adaptive wavelet packet basis is selected for representing the given image using certain entropy-based cost functions. Second, the wavelet packet coefficients are quantized using an optimal scalar quantizer for Laplacian distribution. Third, the quantized coefficient is represented with stack-run coding generating a redundant symbol stream. Finally, this symbol stream is entropy coded using a higher order arithmetic coder.

Effect of heating cycle on the structure of Ag films deposited over porcelain substrates

Abstract: Silver films were deposited over porcelain substrates by using flexible adhesive transfer layers. These films were produced in order to use porcelain utensils over household induction heating plates. Mixtures of different glass ceramic powders with silver powder are used to prepare the self-transfer patterns. These patterns are deposited over porcelain substrates and sintered using different heating cycles. One defect observed in such films is the presence of porosity either at the Ag/porcelain interface or inside the Ag film structure. While lower sintering temperatures produce less porosity, the microstructure of the Ag layer at lower temperatures is no longer composed of a contiguous network of large silver agglomerates. Consequently, the heating capability of the layer through electromagnetic induction is affected. Finally a sintering cycle is proposed for which the film properties are least modified with a minimum level of porosity.

Rapid Aircraft Classification in Satellite Imagery using Fully Convolutional Residual Network

Abstract: Advancement in high-performance computing technology has paved way for development of Deep Learning algorithms for computer vision to provide unprecedented performance both in terms of accuracy and speed. Image recognition, a subfield of computer vision, is one of the key application areas in which deep learning based Convolutional Neural Networks (CNN have achieved ground-breaking performance). Majority of the algorithms of object classification in CNN are focused on street view imagery that is of high resolution and have small size. The problem with satellite imagery is that it has objects in small size and images are especially in large size. There are two main objectives of this research: time reduction of processing large dimensions satellite images, and achieving acceptable accuracy of classifying small aircrafts. For this purpose, ResNet-50 has been modified such that it can process high-resolution satellite imagery of large dimension in one go instead of processing it in small patches sequentially, without affecting the accuracy of object classification. ResNet-50 with sliding-window scanning technique and the proposed model trained on satellite imagery are compared. The proposed method reduces the processing time by 99.9% by keeping the accuracy at the same level.

Steady Streaming Due to Transverse Vibration and Torsional Oscillation of a Cylinder

Abstract: In this paper steady streaming due to small-amplitude transverse vibrations and torsional oscillation of a cylinder in an infinite viscous incompressible fluid is studied The Vishik–Lyusternik method is employed to construct an asymptotic expansion of the solution of the Navier–Stokes equations in the limit of high-frequency vibrations for Reynolds numbers of order of 1 The effect of the Stokes drift of fluid particles is also considered

Nuclear inputs of key iron isotopes for core-collapse modeling and simulation

Abstract: From the modeling and simulation results of presupernova evolution of massive stars, it was found that isotopes of iron, , play a significant role inside the stellar cores, primarily decreasing the electron-to-baryon ratio () mainly via electron capture processes thereby reducing the pressure support. The neutrinos produced as a result of these capture processes are transparent to the stellar matter and assist in cooling the core, thereby reducing the entropy. The structure of the presupernova star is altered both by the changes in and the entropy of the core material. Here we present the microscopic calculation of Gamow–Teller strength distributions for isotopes of iron. The calculation is also compared with other theoretical models and experimental data. Presented also are stellar electron capture rates and associated neutrino cooling rates, due to isotopes of iron, in a form suitable for simulation and modeling codes. It is hoped that the nuclear inputs presented here should assist core-collapse simulators in the process of fine-tuning of the parameter during various phases of presupernova evolution of massive stars. A reliable and accurate time evolution of this parameter is a possible key to generate a successful explosion in modeling of core-collapse supernovae.