Ijaz Ali, Amjid Iqbal, Arshad Mahmood, A. Shah, M. Zakria and Asad Ali
Cd1−xZnxSe (x = 0, 0.40 and 1) thin films were deposited on a glass substrate at room temperature by closed space sublimation method. Optical investigation has been performed using spectrophotometry and ellipsometry. It has been found that for as deposited films the optical band gap increased and the optical constants decreased with increasing Zn content. To improve the optical properties of Cd1−xZnxSe thin films annealing effect at 400 °C was taken into consideration for various Zn contents. It was observed that the optical transmittance and band gap decreased while optical constants increased with increasing Zn content after annealing. The effects of composition and annealing on the optical dispersion parameters Eo and Ed were investigated using a single effective oscillator model. The calculated value of the average excitation energy Eo obeys the empirical relation (Eo = Eg/2) obtained from the single oscillator model.
Asad Gulzar, Mahmood Ahmed, Muhammad Abdul Qadir, Muhammad Imtiaz Shafiq, Sakhawat Ali, Ijaz Ahmad and Muhammad Farooq Mukhtar
The present invention was undertaken to study and determine the effect of potassium metabisulphite (6%) and potassium sorbate (350 ppm) treatments on the nutritional quality of osmotically-dehydrated, infrared- and microwave-blanched dried mango slices (local cultivars “Chaunsa” and “Fajri”) stored for the period of 6 months under ambient conditions. The studied parameters included physical characteristics such as water activity, non-enzymatic browning, and color values, chemical parameters such as moisture, ash, fiber, acidity and content of proteins, sugars, vitamin C, total carotenoids, and sensory attributes such as appearance, flavor and texture. Vitamin C content in osmotically-dried mango slices was higher than that of IR and MW blanched dried mango slices but the content of vitamin C of both cultivars was lower than of the fresh mango samples (Chaunsa: 135 mg/100 g, Fajri: 94 mg/100 g). Significant loss was noticed in total carotenoids content of both the cultivars with passage of time because of their susceptibility to oxidative loss caused by dry heat. No growth of yeast and mold was detected in potassium sorbate-treated dried mango slices due to their preservative effect. From the point of view of the composition and sensory quality, dried mango slices of both the cultivars have excellent nutritional qualities.
Stylometric authorship attribution aims to identify an anonymous or disputed document’s author by examining its writing style. The development of powerful machine learning based stylometric authorship attribution methods presents a serious privacy threat for individuals such as journalists and activists who wish to publish anonymously. Researchers have proposed several authorship obfuscation approaches that try to make appropriate changes (e.g. word/phrase replacements) to evade attribution while preserving semantics. Unfortunately, existing authorship obfuscation approaches are lacking because they either require some manual effort, require significant training data, or do not work for long documents. To address these limitations, we propose a genetic algorithm based random search framework called Mutant-X which can automatically obfuscate text to successfully evade attribution while keeping the semantics of the obfuscated text similar to the original text. Specifically, Mutant-X sequentially makes changes in the text using mutation and crossover techniques while being guided by a fitness function that takes into account both attribution probability and semantic relevance. While Mutant-X requires black-box knowledge of the adversary’s classifier, it does not require any additional training data and also works on documents of any length. We evaluate Mutant-X against a variety of authorship attribution methods on two different text corpora. Our results show that Mutant-X can decrease the accuracy of state-of-the-art authorship attribution methods by as much as 64% while preserving the semantics much better than existing automated authorship obfuscation approaches. While Mutant-X advances the state-of-the-art in automated authorship obfuscation, we find that it does not generalize to a stronger threat model where the adversary uses a different attribution classifier than what Mutant-X assumes. Our findings warrant the need for future research to improve the generalizability (or transferability) of automated authorship obfuscation approaches.