Browsing by Author "Bashir, S.A."

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    A Survey of Cloud Computing Awareness, Security Implication and Adoption in Nigeria IT Based Enterprises
    (Faculty of Communication and Information Sciences, University of Ilorin, Ilorin, Nigeria - International Journal of Information Processing and Communication, 3(1&2), 210 – 220, 2015) Bashir, S.A.; Adebayo, O.S.; Abdulsalam, S.O.; Sadiku, J.S.; Mabayoje, M.A.
    The advancement in information technology (IT) infrastructures and the overwhelming pervasive Internet accessibility has tremendously change the way computing is done in IT based enterprises. The recent hype of Cloud Computing that utilizes the existing Internet infrastructure to provide pay-as-you-go services to diverse community of businesses has emerged to alleviate and reduce the cost of computing tremendously. This paper examined the awareness of the Nigerian business enterprisesand their readiness in adopting cloud computing. It was found that the trend of awareness and adoption were very minimal with many being sceptical although few businesses were aware of the cloud technology. The survey also revealed that the stakeholders were precarious of the security-level of the cloud-based computing. Keywords: Cloud-Based Computing, Security Implications, Cloud Awareness, Cloud Adoption, Enterprises, Technology
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    Agent-Based Faults Monitoring in Automatic Teller Machines
    (African Institute of Development Informatics and Policy - Computing, Information Systems and Development Informatics Journal, 3(4), 1 – 6, 2012) Bashir, S.A.; Mohammed, I.K.; Abdulsalam, S.O.
    Automated Teller Machine (ATM) has gained widespread acceptance as a convenient medium to facilitate financial transaction without need for human agent. However, ATM deployers are facing challenges in maximizing the uptime of their ATMs as a result of wide gap in fault detection, notification and correction of the ATMs. One way to ameliorate this situation is through intelligent monitoring of ATM by resident software agents that monitor the device real time and report faulty components real time to facilitate quick response. We proposed an architecture for rule-based, intelligent agent based monitoring and management of ATMs. Agents are used to perform remote monitoring on the ATMs and control function such software maintenance. Such agents can detect basic events or correlate existing events that are stored in a database to detect faults. A system administrator can securely modify the monitoring policies and control functions of agents. The framework presented here includes software fault monitor, hardware fault monitor and transaction monitor. A set of utility support agents: caller agent and log agent are used to alert network operator and log error and transaction information in a database respectively. at-1, stuck-at-0 faults in digital circuits validate the point that faulty circuits dissipates more and hence draw more power. Key words: Automated Teller Machine (ATM), Intelligent Agents, Mobile Agents, Event Monitoring
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    Data Mining for Knowledge Discovery from Financial Institution Database
    (Society for Science and Nature - International Journal of Engineering and Management Sciences. 3(4), 409 – 415, 2012) Abdulsalam, S.O.; Adewole, K.S.; Bashir, S.A.; Jimoh, R.G.; Olagunju, M.
    Due to its importance for the investment decision-making and risk management, describing and predicting stock represents a key topic in stock analysis. Stock or shares are valued and analyzed by stock investors using fundamental analysis and technical analysis. Stock investors describe and predict stock manually based on individual experiences. Employing manual procedure in analyzing stock, most especially technical analysis is always very cumbersome and inefficient; because of much time that is consumed in examining the past records of a respective firm, an investor is willing to invest in. This paper presents a better way of describing and predicting stock, especially technical analysis, by employing data mining techniques. A database was developed employing 360 records of daily activity summary (equities) and 78 records of weekly activity summary (equities) spanning through 18 months that is, from January 2007 to June 2008. These data were obtained from the daily official list of the prices of all shares traded on the stock exchange published by the Nigerian Stock Exchange being the financial institution that runs Nigerian stock market; using banking sector of Nigerian economy with three banks namely:- First Bank of Nigeria Plc, Zenith Bank Plc, and Skye Bank Plc. A data mining software tool was developed and employed in identifying patterns and relationships from the database to generate new knowledge about the data set in the database through the use of data mining techniques that employ regression analysis. KEYWORDS: Data Mining, Stock Exchange, Financial Institution, Decision-Making, Risk Management, Regression Analysis