Number of security vulnerabilities in web application has grown with the tremendous growth of web application in last two decades. As the domain of Web Applications is maturing, large number of empirical studies has been reported in web applications to address the solution of vulnerable web application. However, before advancing towards finding new approaches of web applications security vulnerability detection, there is a need to analyze and synthesize existing evidence based studies in web applications area. To do this, we have planned to conduct a systematic mapping study to view and report the state-of-the-art of empirical work in existing research of web applications. In this paper, we aimed at providing a description of mapping study for synthesizing the reported empirical research in the area of web applications security vulnerabilities detection approaches. The proposed solutions are mapped against: (1) the software development stages for which the solution has been proposed and (2) the web application vulnerabilities mapping according to OWASP Top 10 security vulnerabilities.To do this, existing literature has been surveyed using a systematic mapping study by phrasing two research questions. In the mapping study, a total of 41 studies dating from 1994 to 2014 were evaluated and mapped against the aforementioned categories.The outcome of this mapping study is current state-of-the-art of empirical research in web application area, strength and weaknesses of existing empirical work, best practices and possible directions for future research.

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A facile green method is used to synthesize silver nanoparticles (Ag Nps) in one minute. The colloidal stability of two types of Ag Nps (namely, hydroxypropylcellulose-succinate (HPC-Suc) capped silver nanoparticles (Ag Nps@suc) and citrate-capped silver nanoparticles (Ag Nps@cit)) is investigated using UV-Vis spectrometry and electrochemical particle impacts “nano-impacts” measurements. Ag Nps@suc were newly synthesized by simply mixing aqueous solutions of HPC-Suc and silver nitrate and exposure to sunlight. The growth of Ag Nps was controlled by adjusting the exposure time to sun light. Local surface plasmon resonance (LSPR) study was conducted using UV-Vis spectrophotometer. The surface morphology, size, elemental analysis and composition of Ag NPs@suc was determined by SEM-EDX, while ATR-FTIR was used to assess any type of chemical reactions between the precursors. For stability and size distribution measurements zeta-potential (ZP), dynamic light scattering (DSL) and anodic particle coulometry (APC) were performed. The as-prepared Ag Nps@suc exhibited a narrow size distribution with an average diameter of 20 nm. Nps sizing using particles electrochemical impacts method is consistent with SEM and DLS techniques. The results show that Ag Nps@cit are prone to relatively rapid clustering upon addition of electrolyte (100 mM K2SO4). On the other hand, Ag Nps@suc exhibit excellent stability with only ~ 9% decay in absorbance over 24 h even at high electrolyte concentration. Using KCl, KBr and NaCl electrolytes, the stability of the synthesized Ag Nps@suc also compares favorably to Ag Nps@cit.

Product evaluations, ratings, and other sorts of online expressions have risen in popularity as a result of the emergence of social networking sites and blogs. Sentiment analysis has emerged as a new area of study for computational linguists as a result of this rapidly expanding data set. From around a decade ago, this has been a topic of discussion for English speakers. However, the scientific community completely ignores other important languages, such as Urdu. Morphologically, Urdu is one of the most complex languages in the world. For this reason, a variety of unique characteristics, such as the language's unusual morphology and unrestricted word order, make the Urdu language processing a difficult challenge to solve. This research provides a new framework for the categorization of Urdu language sentiments. The main contributions of the research are to show how important this multidimensional research problem is as well as its technical parts, such as the parsing algorithm, corpus, lexicon, etc. A new approach for Urdu text sentiment analysis including data gathering, pre-processing, feature extraction, feature vector formation, and finally, sentiment classification has been designed to deal with Urdu language sentiments. The result and discussion section provides a comprehensive comparison of the proposed work with the standard baseline method in terms of precision, recall, f-measure, and accuracy of three different types of datasets. In the overall comparison of the models, the proposed work shows an encouraging achievement in terms of accuracy and other metrics. Last but not least, this section also provides the featured trend and possible direction of the current work.

S1 UV-Vis spectrophotometryA solution of AgNO3 and HPC-Suc was exposed to sunlight and the synthesis of the Ag NPs@suc in aqueous solution was monitored periodically (after an exposure time of 15 s, 30 s, 60 s, 90 s, 105 s, 120 s and 25 min) by recording the absorption spectra over a wavelength range of 300-800 nm.Upon exposure to sunlight during an initial period of 15 s to 25 min, the Ag + was reduced to Ag Nps@suc and color of solution changed from light yellow to reddish brown. A single and broad LSPR peak was observed in the range 411-452 nm, confirming the synthesis of Ag Nps (Figure S1) (Mulvaney, 1996). This LSPR absorption peak showed a red shift in λmax and an increase in the intensity of absorption upon the increase of exposure time to sunlight, which suggests that the size of the Ag Nps@suc increases with an increase in exposure or reaction time (Abbas et al., 2015;Ding et al., 2017).