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.

Stimulating student’s pro-environmental behavior in higher education institutions: an ability–motivation–opportunity perspective

Abstract: The slow and inadequate environmental performance of higher education institutions is attracting the consideration of researchers toward a behavioral change of teachers and students rather than just concentrating on learning and technology adoption. Based on the ability–motivation–opportunity (AMO) theory, this research aims to explore a relationship between green human resource management practices (i.e., ability, motivation, and opportunity) with student’s pro-environmental behavior (PEB). The environmental knowledge as a mediator and the leader’s support as a moderator are examined in the developed relationship. Then, the model is analyzed among students of public universities in Pakistan. It has been observed that green AMO-enhancing practices are significantly affecting the student's PEB and environmental knowledge considerably mediates these associations. Moreover, the leader’s support moderates the effect of green ability-enhancing practices and green opportunity-enhancing practices on student’s PEB. The current study not only contributes to green human resource management research but also provides significant implications for decision makers to develop policies for a sustainable environment in higher education institutions of Pakistan.

A Fast Non-Redundant Feature Selection Technique for Text Data

Abstract: Feature selection is critical in reducing the size of data and improving classifier accuracy by selecting an optimum subset of the overall features. Traditionally, each feature is given a score against a particular category (such as using Mutual Information) and the task of feature selection comes down to choosing the top $k$ ranked features with the best average score across all categories. However, this approach has two major drawbacks. Firstly, the maximum or average score of a feature with a class might not necessarily determine its discriminating strength among samples of other classes. Secondly, most feature selection methods only use the scores to select the discriminating features from the corpus without taking into account the redundancy of information provided by the selected features. In this paper, we propose a new feature ranking score measure called the Discriminative Mutual Information (DMI) score. This score helps to select features that distinguish samples of one category against all other categories. Moreover, Non-Redundant Feature Selection (NRFS) heuristic is also proposed that explicitly takes the problem of feature redundancy into account when selecting the features set. The performance of our approach is investigated and compared with other feature selection techniques on datasets derived from high-dimensional text corpora using multiple classification algorithms. The results show that the proposed method leads to better classification micro-F1 score as compared to other state-of-the-art methods. In particular, the proposed method shows great improvement when the number of selected features are small as well as an overall higher robustness to label noise.

Improved organic solar cell by incorporating silver nanoparticles embedded polyaniline as buffer layer

Abstract: The role of silver nanoparticles (AgNP) in polyaniline (PANI) as a buffer layer for ITO/AgNP-PANI/PANI/Al solar cell was investigated. It is observed that AgNP-PANI buffer layer significantly improves the electrical parameters such as diode-ideality factor, series-resistance, energy-barrier height, and shunt-resistance as a growing function of AgNP concentration. On-the-other hand oppose to the dark current-voltage response, 0.5% concentration of AgNP in buffer layer shows the most optimum photovoltaic response and cause to increase the power conversion efficiency (PCE) nearly 5 times compared to same solar cell without buffer layer. Such improvements in electrical parameters can be interpreted as the reduction in interfacial trap states as well as enhancement in interfacial dipole-moment by AgNP embedded buffer layer for given photovoltaic device. While, the observed optimum photovoltaic behavior at 0.5% AgNP concentration is may be due to the trade-offs between gains and losses for optical absorption enhancement, self-absorption heating and interface recombination losses respectively. It is also observed that the AgNP embedded PANI buffer layer approach is an effective solution to lower the photovoltaic degradation and hence improves the stability of the photovoltaic devices.