This paper proposes a portable learning framework that uses cell phones and Near Field Communication (NFC) innovation in which this application permits understudies to connect with genuine questions and get data from the labels that are put on the item by filtering the tag put on the article. These gimmicks empower the learning procedure at all over the place (pervasive learning) and enhance the viability of the learning methodology. In this paper, Mobile Application Development Lifecycle (MADLC) model was utilized to safeguard effective M-Lang framework conveyance. M-lang framework clients are required to utilize cell phones to advance the involvement in Malay Language learning.

Social media is a collection of computer-mediated technologies that encourages the creation and sharing of data, thoughts and vocation interests by means of online communities. There are various kinds of web-based social networking i.e. micro-blogs, wikis and social networking sites. Different social media like Facebook, LinkedIn, Google+ and Twitter are the popular sources for connecting people all over the globe. Facebook is one of the commonly used platform where individual’s used to stay in touch, business personnel used for marketing and others used to share expedient information. Due to this lucrative nature, one’s personality can be predicted on the basis of posts created, commented on others post and likes against any posts. We have developed in-house tool using python language that defines personality in terms of psychological model of Big-5 personality traits including extraversion, neuroticism, agreeableness, openness and conscientiousness. The dictionary based approach has been used in this tool in which we have combined three dictionaries (WordNet, SenticNet and Opinion Lexicon). Our proposed technique has shown promising results as we have analyzed 213 unique Facebook profiles and their results outperforms the others. Furthermore a comparative analysis of machine learning classifiers i.e. support vector machine, na?ve bays and decision tree has performed. Our approach succeeds to predict personality traits. We are intended to predict personality from roman English posts in future.

The impact of malicious software are getting worse day by day. Malicious software or malwares are programs that are created to harm, interrupt or damage computers, networks and other resources associated with it. Malwares are transferred in computers without the knowledge of its owner. Mostly the medium used to spread malwares are networks and portable devices. Malwares are always been a threat to digital world but with a rapid increase in the use of internet, the impacts of the malwares become severe and cannot be ignored. A lot of malware detectors have been created, the effectiveness of these detectors depend upon the techniques being used. Although researchers are developing latest technologies for the timely detection of malwares but still malware creators always stay one step ahead. In this paper, a detailed review of malwares types are provided, malware analysis and detection techniques are studied and compared. Furthermore, malware obfuscation techniques have also been presented.

Twitter network has millions of users spreading information in the form of 140 character messages called tweets. And each user expresses his or her opinion with the tweet, these tweets have been used to know a person’s state of mind, get recommendations and also predict the pattern. But a research is an effective one only if its results can be easily understood and a clear understanding requires visualization of the inferences. There isn’t any data-graph, pie chart or a tree depicting the results of twitter analysis. Hence this paper suggests “TweetRush” tool to analyze twitter data. It is able to find the influence of a particular user in his network. Graphs help us determine a user’s outreach. This tool will help advertisers to target the exact audience; budding entrepreneurs can make use of the influential factor to market their start-ups.

The concept of smart cities has become very popular in recent times and with much more clear understanding. The evaluation of Internet of things and recent progress in the technology has given smart city project a real lift. IOT models can easily be integrated in different fields and sections of a city to attain a working smart city. Modern Smart city should not only be technologically advanced but must also provide better quality of life and more opportunities improved lifestyle and development for its citizen. This Paper provides us a survey of how Internet of things can help us in the development of a smart city and also identifies the main components and elements characterizing a smart city.
Furthermore we will also discuss the benefits a society will get from the working smart city project.

This paper shows an analysis of features of email system using feature model in a Software Product Line (SPL). The core features that can be used by different SPLs are identified using feature model. The analysis is based on two primary measures – reusability and consistency. Reusability measures the level of frequency of usage of the feature in developing a new software product line and consistency ensures that the core features are consistent in a software product line. On the basis of reusability measure, the core features are classified into four different categories. These measures help in understanding the Return on Investment in a software product line.