The demand for data-driven decision making has resulted in the application of data mining in the educational sector and other disciplines. The needs for improving the performance of data mining models have been identified as an interesting area of research institutions keep a large amount of students' data, but these data are rarely used effectively in decision and or policy-making processes. This research is an attempt to enhance the performance of data mining models to predict ensemble and synthetic minority over IBK and SMO were trained and tested on 206 students' data set using previous academic performance records of Federal University Dutse, Nigeria. WEKA 3.9.1 data mining tool was used in predicting the final year student's classes of degree at an undergraduate level, while Unified Tertiary Matriculation Examination, Senior Secondary Certificate Examinations Cumulative Grade Point Average of students served as inputs to the model. The result obtained showed that on training dataset after class balancing, performing the other three (3) classifiers models in RSME (0.1098), suggesting that stacking classifiers ensemble is the best model in context of this research.

This research work describes the software development of an integrated wireless sensor network (WSN) for realtime remote monitoring of oil and gas flow rate metering infrastructure. The wireless sensor network includes flow sensors, pumping machines, microcontrollers, Wi-Fi or wireless links and a database server. The pumping machine first pumps oil and gas, then a flow rate sensor measures the quantity and communicates the flow rate data in meter cube per second via a wireless link to the database server for further processing. The resulting data is stored on the database server while the continuous flow rate is displayed in real time on the website designed as the humancomputer interaction (HCI) interface through which, the quantity of the oil and gas lifted can easily be accessed without having to collect the data from several stations manually. The cost-effective indices for reporting the quantity of oil and gas lifting are of significance to any accountable and transparent system. However, manual processes have not been able to do that in real time. In this paper, our main focus is to provide the software development life cycle involved in the design and implementation processes of the system prototype using iterative incremental mode and the complete software development architecture for the wireless sensor network.