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Institution

Ghulam Ishaq Khan Institute of Engineering Sciences and Technology

EducationTopi, Pakistan
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.


Papers
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Journal ArticleDOI
TL;DR: In this article, the Fortschritte bei elektrochemischen and photoelektrokatalytischen Wasserspaltungssystemen vorgestellt, die sowohl Wasser oxidierende molekulare Komplexe al as well as auch nanostrukturierte Anordnungen zur Entwicklung eines knstlichen Photosyntheseapparats nutzen.
Abstract: Die Erschliesung von erneuerbaren Ressourcen zur Herstellung sauberer Brennstoffe aus reichlich vorhandenen und einfach zugng- lichen Ressourcen zhlt derzeit zu den anspruchsvollsten Aufgaben der Wissenschaft. Katalytische Prozesse zur Wasserspaltung mithilfe von Solarenergie kcnnen als Quelle fr Elektronen und Protonen zur Erzeugung sauberer Brennstoffe wie Wasserstoff sowie zur Seques- trierung von CO2 und dessen Umwandlung in kohlenstoffarme En- ergietrger genutzt werden. In letzter Zeit wurden grose Anstren- gungen unternommen, um ein eigenstndiges Element zur Umwand- lung von Solarenergie in Brennstoff zu bauen: ein "knstliches Blatt", das mit Licht und Wasser als Rohstoffen arbeitet. Hier werden jngste Fortschritte bei elektrochemischen und photoelektrokatalytischen Wasserspaltungssystemen vorgestellt, die sowohl Wasser oxidierende molekulare Komplexe als auch nanostrukturierte Anordnungen zur Entwicklung eines knstlichen Photosyntheseapparats nutzen.

59 citations

Journal ArticleDOI
TL;DR: A digital watermarking technique is proposed which avoids the distortion of image in ROI by embedding the watermark information in RONI.
Abstract: Image processing techniques have played a very significant role in the past decades in the field of medical sciences for diagnosis and treatment purposes. In some applications, medical images are divided into region of interest (ROI) and region of non-interest (RONI). Important information regarding diagnosis is contained in the ROI, so its integrity must be assured. We propose a fragile watermarking technique to ensure the integrity of the medical image that avoids the distortion of the image in ROI by embedding the watermark information in RONI. The watermark is composed of patient information, hospital logo and message authentication code computed using a hash function. Earlier encryption of watermark is performed to ensure inaccessibility of embedded data to the adversaries.

59 citations

Journal ArticleDOI
TL;DR: Magnetic molecularly imprinted polymer (mag-MIPs) were developed for the analysis of ametryn (4-N-ethyl-6-methylsulfanyl-2-Npropan 2-yl-1,3,5-triazine-2,4-diamine), a popular triazine herbicide as mentioned in this paper.
Abstract: Magnetic molecularly imprinted polymer (mag-MIP) were developed for the analysis of ametryn (4-N-ethyl-6-methylsulfanyl-2-N-propan-2-yl-1,3,5-triazine-2,4-diamine), a popular triazine herbicide. Iron oxide (Fe3O4) nanoparticles were synthetized, and then modified with tetraethoxysilane (TEOS) and 3-mercaptopropyltrimethoxysilane (MPS). Then MIPs' polymerimerization occurred in the nanoparticles' surface, using ethylene-glycol-dimethacrylate (EGDMA) as the building monomer, 2,2′-azobis(2-methylpropionitrile) (AIBN) as the radical initiator, and 2-vinylpyridine as the functional monomer. The functional monomer was previously chosen by computational simulation. The mag-MIPs' adsorption behavior well-fitted a Langmuir model (qm of 8.6 mg g− 1, KL of 5.2 L mg− 1) and pseudo first order kinetics (k1 of 2.5 × 10− 4 s− 1). The developed analytical methodology, using high-performance liquid chromatography with UV detection (HPLC-UV), showed suitable selectivity and had a limit of detection (LOD) and quantification (LOQ) of 25 and 82 nmol L− 1, respectively.

58 citations

Journal ArticleDOI
TL;DR: A cell association scheme that selectively mutes certain small-cell base stations and covers end users by cell range extension (via cell biasing) for achieving load balancing and a signal-to-interference plus noise ratio (SINR) distribution are proposed.
Abstract: To meet the ever-growing traffic demand and address the cell capacity shortage problem, associating end users to various tiers of cells in a multitier cellular network appears to be a promising approach. In this paper, we consider a nonuniform heterogeneous cellular network (NuHCN) and propose a cell association scheme that selectively mutes certain small-cell base stations (BSs) and covers end users by cell range extension (via cell biasing) for achieving load balancing. The envisaged NuHCN is comprised of two tiers of BSs, i.e., macro- and small-cell BSs, deployed according to three independent homogeneous Poisson point processes for BSs and end users, respectively. Accordingly, the available space is divided into two subspaces. In the inner subspace, the end users are associated only with a macrocell BS based on the unbiased maximum received power scheme since the small-cell BSs therein are deactivated. In the outer subspace, where the macrocell BS coverage is comparatively poor, the end users are associated with either a macrocell BS or a microcell BS based on the biased/unbiased maximum received power scheme. Cell range extension-based cell association allows the macrocell users in the outer subspace to efficiently utilize the resources of the lightly loaded small-cell BSs, resulting in improved network coverage and capacity. Based on the proposed cell association scheme, we analyze the signal-to-interference plus noise ratio (SINR) distribution and deduce expressions for coverage probability and rate coverage. Numerical results show that, contrary to the uniform case, biasing has distinct effects on the coverage and rate performance of an NuHCN.

58 citations


Authors

Showing all 626 results

NameH-indexPapersCitations
Wajid Ali Khan128127279308
Shuichi Miyazaki6945518513
Muhammad Zubair5180610265
Mohammad Islam441929721
Asifullah Khan381925109
Muhammad Waqas323837336
Rana Abdul Shakoor301403244
Noor Muhammad291602656
Abdul Majid282313134
Muhammad Abid273773214
Iftikhar Ahmad261432500
Shaheen Fatima24792287
Ghulam Hussain241271937
Zubair Ahmad241451899
Muhammad Zahir Iqbal231291624
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20235
20229
2021180
2020154
2019100
201863