This study is devoted to evaluating the security risk analysis and management in Online Banking transactions using Diamond Bank PLC, Nigeria among other banks. In this paper, a research was carried out in order to evaluate the security risk analysis and management in online banking transactions through the use of the questionnaire to determine the level of risk that customers of financial institutions are likely to encounter. The study indication shows that awareness need to be intensified in terms of risk associated with clients saving password and other transaction details in their devices used in performing an online transaction. Also, the bank should improve on their banking transaction application in order to maintain integrity in view of customer account information.

With advent of technology online education has become the core of educational settings worldwide. This paper aims to identify the factors that contribute in enhancing the online learning usage model in context of India, an emerging leader in Educational settings across the globe. In this study, data mining techniques were applied on the data collected from the log files of online courses. The initial investigations supported the use of custom build framework for teaching online courses. Data Structure course was taught using online platform and the data was collected using the log files. The data collected was further analysed using data mining techniques using Rapid miner tool. Although the results from three different data mining techniques showed some variations but the inferences from the results identified few common factors that have influence on enhancing the online learning usage model. Clustering techniques revealed that factors related to timely checking of online contents and posting have positive impact on online learning however decision trees supported that timely completing the online assignments along with checking of online contents and posting of messages played an important role in terms of enhancing the academic performance. This paper identifies three factors for teachers teaching online courses to improve overall performance of the students by learning from Indian University Success.

Currently, modern social technologies are used by hundreds of millions of users, are available free of charge, attractive and interesting. The article discusses the possibility of the use of social networks to improve e-learning institution of higher education. Considering the large amount of information disseminated by university students on the social network, it is proposed to use methods of data clustering - k-means (k-means) in the article, to personalize the content of educational materials. The results of the research can be used by teachers and instructors of higher education institutions to improve the content of the e-course and personalize e-learning.

The universes’ most complex structure is the human brain. To analyze its characteristics, many studies and experiments have been carried out in a proper and systematic manner. From these researches and experiments, scientists have learnt to communicate with computer using brain and hence, BCI has been developed. A Brain-Computer Interface (BCI) provides a communication path between the human brain and the computer system. With the advancement of information technology and neuroscience, there has been a flow of interest in turning fiction into reality. This research investigated existing works of BCI with the purpose developing a system that allows physically challenged people to communicate with other persons and helps to interact with the external environments with the help of computers. Components like, comparison of invasive and non-invasive technologies to measure brain activity, evaluation of control signals (i.e. patterns of brain activity or brain waves that can be used for communication), development or improvement of algorithms for translation of brain signals into computer commands, specific frequency components like electroencephalography (EEG), artificial neural network (ANN) etc. are used to accomplish such a feat. With such, the developments of new BCI applications are emerging every day.

Chronic kidney disease is an important challenge for health systems around the world and consuming a huge proportion of health care finances. Around 85% of the world populations live in developing country of the world, where chronic kidney disease prevention programs are undeveloped. Treatment options for chronic kidney disease are not readily available for most countries in sub-Saharan Africa including Ethiopia. Many rural and urban communities in Ethiopia have extremely limited access to medical advice where medical experts are not readily available. To address such a problem, a medical knowledge-based system can play a significant role. Therefore, the aim of this research was developing a self- learning knowledge based system for diagnosis and treatment of the first three stages of kidney disease that can update the knowledge without the involvement of knowledge engineer. In the development of this system, the following procedures are followed: Knowledge Engineering research design was used to develop prototype system. Purposive sampling strategies were utilized to choose specialists. The information was acquired by using both structured and unstructured interviews and all knowledge’s are represented by using production rule. The represented production rule was modeled by using decision tree modeling approach. Implementation was employed by using pro-log tools. Testing and evolution was performed through test case and user acceptance methods. Finally, we extensively evaluate the prototype system through visual interactions and test cases. The test results show that our approach is better to the current ones.