E-learning is a convenient way of learning through a portal. E-learning is being increasingly adopted in the world; however, the factors that influence the intention of users for accepting the e-learning technology have not been sufficiently explored, particularly in developing countries. Although many e-learning acceptance models do exist, the research on a user experience (UX)-based e-learning acceptance model is still lacking. As UX is one of the crucial factors for the acceptance of an e-learning portal, this research study aims to develop and validate a UX-based e-learning acceptance framework for sustainable higher education. In this connection, a web-based responsive e-learning portal for university students has been developed. The portal can be accessed from anywhere, at any time, and on any device, making the learning sustainable. The UX-based e-learning acceptance framework is developed by integrating the selected constructs of a widely accepted UX model, technology acceptance model (TAM), and four well-known constructs from various technology acceptance models. The constructs are appeal, pleasure, satisfaction, perceived ease of use, perceived usefulness, information quality, self-efficacy, social influence, benefits, and behavioral intention, which can predict the intentions of the students for acceptance of the e-learning portal. The data were collected from 650 university students using online and manual questionnaires. After data screening, 513 valid responses were further analyzed using structural equation modeling. According to the results, the framework fits the data well. The constructs satisfaction, perceived ease of use, perceived usefulness, information quality, self-efficacy, social influence, and benefits have a statistically significant effect on the behavioral intention of the students regarding the acceptance of the e-learning portal. The construct perceived ease of use has a statistical significant impact on perceived usefulness and pleasure. The construct appeal has a statistical significant impact on pleasure and satisfaction. Similarly, the construct pleasure has also a positive statistical significant impact on satisfaction. This research study contributes to the e-learning acceptance models by developing and validating the UX-based e-learning acceptance framework for sustainable higher education. The framework provides important insights for the acceptance of university based e-learning portals in the context of developing countries.

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In this paper, image noise is removed by using a hybrid model of wiener and fuzzy filters. It is a challenging task to remove Gaussian noise (GN) from an image and to protect the image’s edges. The Fuzzy-Wiener filter (FWF) hybrid model is used for optimizing the image smoothness and efficiency at a high level of GN. The efficiency is measured by using Structural Similarity (SSIM), Mean Square Error (MSE), and Peak Signal to Noise Ratio (PSNR). The proposed algorithm substitutes a mean value of the matrix for a non-overlapping block and replaces the total pixel number with each direction. In the proposed model, overall results proved that the optimized hybrid model FWF has an enormous computational speed and impulsive noise reduction, which enables efficient filtering as compared to the existing techniques.

The Internet is not safe anymore, malware can be discovered anywhere on the Internet. The risk of malware has increased also due to the increasing popularity and use of Smartphones and their underlying cost-free applications. With its great market share, the Android operating system has become a prime target for malware developers. When an Android phone is injected with a malware, it may result in compromising the privacy of the user by stealing sensitive and private information like contacts, ids, passwords, photos, call records, and so on. Compared to any other Android-based application category, games are the most preferred zone for attackers, due to the high interest of users in game applications. When an end user downloads a game, which is injected with malicious code, user data is infected without bringing in the knowledge of the user. Though, there still are not sufficient protection mechanisms or guidelines stated for end user against Android malware, this study offers a novel approach to detect Android malware in order to ensure the safe usage of Android applications. The advantage of this approach is its ability to utilize Android manifest files for the detection of malware. The availability of manifest file in every Android application makes this approach applicable to all Android applications. It can also be considered as a lightweight method for malware detection, and its efficiency is experimentally confirmed by testing and comparing the results of 50 Android games samples. Experiments are carried out using the Android Package Kit (APK) tools, and based on the experiments, different kinds of malware identification and prevention guidelines have been proposed for the safe and secure usage of the Android operating system.