This study basically investigates the current motivation to use Facebook as a supportive tool for e-learning in a higher education institute of Pakistan. Faculty interviews are conducted to collect the opinions about Facebook as learning and teaching tool. Also statistics on a subject based Facebook page and a group designed for undergraduate students are presented. It has been concluded that Facebook can play its role to facilitate e-learning as more than a social networking website. It is analysed that participation and engagement of students on Facebook page and group is quite optimistic to use it as a supportive tool in future. Results can also help learners and teachers to understand the importance and effects of using social networking website for e-learning.

This research is on the use of a decision tree approach for predicting students' academic performance. Education is the platform on which a society improves the quality of its citizens. To improve on the quality of education, there is a need to be able to predict academic performance of the students. The IBM Statistical Package for Social Studies (SPSS) is used to apply the Chi-Square Automatic Interaction Detection (CHAID) in producing the decision tree structure. Factors such as the financial status of the students, motivation to learn, gender were discovered to affect the performance of the students. 66.8% of the students were predicted to have passed while 33.2% were predicted to fail. It is observed that much larger percentage of the students were likely to pass and there is also a higher likely of male students passing than female students.

Identification of Personality is a complex process. Personality traits are stable over time .Individual's behavior naturally varies from occasion to occasion. But there is a core consistency which defines the true nature. The paper addresses this issue of behavior. Graphology is normally a technique used to identify the traits. Accuracy of this technique depends on how skilled the analyst is. Although human intervention in handwriting analysis has been effective, but it is costly and prone to fatigue. An automation of handwritten text is proposed. Basically we have considered three important features in the direction of orientation of the lines :(i) up hill (ii) down hill (iii) constant line. Edge histogram and bounding boxes was used for feature extraction .Known classifiers like SVM & ANN are used for training and the results were compared. The results were about 98% for SVM & 70% with ANN. The analysis was done using single line.

Cloud computing is an emerging paradigm which has become today's hottest research area due to its ability to reduce the costs associated with computing. In today's era, it is most interesting and enticing technology which is offering the services to its users on demand over the internet. Since Cloud computing stores the data and its disseminated resources in the environment, security has become the main obstacle which is hampering the deployment of cloud environments. There are number of users used cloud to store their personal data, so that data storage security is required on the storage media. The major concern of cloud environment is security during upload the data on cloud server. Data storage at cloud server attracted incredible amount of consideration or spotlight from different communities. For outsourcing the data there is a need of third party. The importance of third party is to prevent and control unauthorized access to data store to the cloud. This research paper discuss the security issues of cloud storage.