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: Quantum efficiency & Diode. The organization has 618 authors who have published 940 publications receiving 10674 citations.

Degradation effect of Auger recombination and built-in polarization field on GaN-based light-emitting diodes

Abstract: In this work, theoretical investigation of the influence of Auger recombination coefficient and built-in polarization field on the internal quantum efficiency (IQE) in terms of lateral-vertical single quantum well (SQW) as well as multiquantum well (MQW) GaN-based blue light-emitting diodes are presented. The degradation effect of the built-in polarization field on the IQE of vertical light-emitting diodes is used to strengthening the Auger recombination coefficient in comparison to lateral light-emitting diodes. This result has been found consistent in both single-as well as multi-quantum well structures. In addition, when Auger recombination coefficient has been included in the analysis, vertical multiquantum well structure shows more degradation in the IQE in comparison to the lateral structures. The effect has been dominant in vertical MQW case.

An effective arrhythmia classification via ECG signal subsampling and mutual information based subbands statistical features selection

Abstract: The deployment of wireless health wearables is increasing in the framework of mobile health monitoring. The power and processing efficiencies with data compression are key aspects. To this end, an efficient automated arrhythmia recognition method is devised. The aim of this work is to contribute to the realisation of modern wireless electrocardiogram (ECG) gadgets. The proposed system utilizes an intelligent combination of subsampling, denoising and wavelet transform based subbands decomposition. Onward, the subband’s statistical features are extracted and mutual information (MI) based dimension reduction is attained for an effective realization of the ECG wearable processing chain. The amount of information to be processed is reduced in a real-time manner by using subsampling. It brings a remarkable reduction in the proposed system's computational complexity compared to the fixed-rate counterparts. MI based features selection improves the classification performance in terms of precision and processing delay. Moreover, it enhances the compression gain and aptitudes an effective diminishing in the transmission activity. Experimental results show that the designed method attains a 4 times computational gain while assuring an appropriate quality of signal reconstruction. A 7.2-fold compression gain compared to conventional counterparts is also attained. The best classification accuracies of 97% and 99% are secured respectively for cases of 5-class and 4-class arrhythmia datasets. It shows that the suggested method realizes an effective recognition of arrhythmia.

Carbon nanotube—cuprous oxide composite based pressure sensors

Abstract: In this paper, we present the design, the fabrication, and the experimental results of carbon nanotube (CNT) and Cu2O composite based pressure sensors. The pressed tablets of the CNT—Cu2O composite are fabricated at a pressure of 353 MPa. The diameters of the multiwalled nanotubes (MWNTs) are between 10 nm and 30 nm. The sizes of the Cu2O micro particles are in the range of 3–4 μm. The average diameter and the average thickness of the pressed tablets are 10 mm and 4.0 mm, respectively. In order to make low resistance electric contacts, the two sides of the pressed tablet are covered by silver pastes. The direct current resistance of the pressure sensor decreases by 3.3 times as the pressure increases up to 37 kN/m2. The simulation result of the resistance—pressure relationship is in good agreement with the experimental result within a variation of ±2%.

A Circuit Analysis-Based Fault Finding Algorithm for Photovoltaic Array Under L–L/L–G Faults

Abstract: At the level of photovoltaic (PV) array inclusive of blocking diodes, line-to-line (L–L) faults and line-to-ground (L–G) faults are difficult to diagnose. These faults may appear at any string of PV array, and if not cleared in time can create irreversible damages to PV modules. In this paper, this complex problem is resolved in two steps: 1) a comprehensive study is presented with the dc circuit analysis of PV array under different faults. The critical observations are summarized in five statements, where each statement is related to a specific fault and 2) a fault-finding algorithm (FFA) based on these statements is proposed. The FFA not only identifies the exact faulty strings but also holds the ability to classify the faults. In the end, the proposed FFA and its five statements are verified through extensive MATLAB/Simulink simulations and numerous experimental tests. Compared to previous studies, the circuit analysis and its five statements are original. Besides that the proposed FFA is simple, fast, requires no training, and scalable to any array size.