Journal of Engineering Research and Reports <p style="text-align: justify;"><strong>Journal of Engineering Research and Reports</strong>&nbsp;<strong>(ISSN: 2582-2926)</strong> aims to publish high-quality papers in all areas&nbsp;of engineering.&nbsp;The journal also encourages the submission of useful reports of negative results. This is a quality controlled,&nbsp;OPEN&nbsp;peer-reviewed, open access INTERNATIONAL journal.</p> SCIENCEDOMAIN international en-US Journal of Engineering Research and Reports 2582-2926 Upgrading Die Attach Machine Capability for Micro Electromechanical Systems Package <p>The paper discussed the study and challenges of the Die Attach process, the critical characteristics of the product structure and the demand for the MEMS product. Upgrading the current machine mechanical and software to improve the machine's capabilities and overcome the criticality of the product structure, such as; 30 microns Die Placement accuracy, can process Wafer with dual Die Orientation 0 and 180 degrees, capable of detecting incorrect die orientation and finally can process thin substrate with 130 microns thickness. After machine upgrades, statistical validation using Two Proportion tests was used to help validate the machine's performance efficiently. The new upgraded machine has the same capability and performance as the new die attach machine model, therefore the upgrade and enhancement on the old model Die Attach machine are effective and efficient.</p> Michael D. Capili ##submission.copyrightStatement## 2020-09-22 2020-09-22 10 15 10.9734/jerr/2020/v17i117178 Development of a Wireless Sensor Network (WSN) Based Energy Efficient Cattle Monitoring System <p>This study shows how to monitor the movement of cattle using wireless sensor nodes powered by a renewable energy source capable of detecting location. Performance analysis was carried out on the energy consumption pattern of the nodes which indicated that throughout the monitoring period, the average energy consumed by the nodes was thus; master node 6450 joules, node one 1680 joules, node two 1656 joules, node three 1676 joules, node four 1656 joules. The rate of energy consumption was sustained by the renewable energy source. It was equally observed that energy consumption increased depending on how often query was sent and how often the conditions of monitoring was violated. This is to guarantee that information about cattle location gets to the base without delay due to battery failure which has been a major challenge faced with the current existing systems in tackling cattle rustling.</p> A. A. Ijah O. W. Bolaji O. O. Adedire J. Z. Emmanuel N. E. Onwuegbunam T. A. Awobona J. A. Ogunsanwo M. S. Likita ##submission.copyrightStatement## 2020-09-17 2020-09-17 1 9 10.9734/jerr/2020/v17i117177 Evapotranspiration Estimation Using Artificial Neural Network over South-Western Nigeria <p>This study was carried out to estimate evapotranspiration over the South-Western region of Nigeria, Artificial Neural Network was used for the estimation of Evapotranspiration over South-Western Nigeria. Using a 36 years meteorological data of South-Western Nigeria obtained from NASA (National Aeronautics and Space Administration) Power data, the Multilayer Perceptron Neural Network and Radial Basis Function Neural Network under several Neural Network Architecture was used, training, testing and validation operations also were performed for estimating evapotranspiration closely to the target calculated value. The performance of each neural network under several NN Architecture was evaluated using statistical indicator such as R (Correlation of Coefficient), R<sup>2 </sup>(Coefficient of Determination), MAE (Mean Absolute Error) and RMSE (Root Mean Square Error). Results present Multilayer Perceptron Neural Network the best neural network with about 70% of its R-values (0.70) because ETo varies in the same pattern as the four of the input parameters used (minimum and maximum air temperature, solar radiation, and wind speed) compare to Radial Basis Network that has 50% of its R-values below (0.70) under several NN Architecture because of the inverse relationship and poor correlation of the ETo and relative humidity. Also, LAGOS and OYO dataset produced the highest performance with an R-value of (0.999998) as a result of uniformity in the climatic trend over 36 years while OGUN dataset produced the lowest performance of (0.467169) as a result of significant variation in the climatic trend over the past 36 years. The study presented here has profound implications for future studies of estimating evapotranspiration and one day help solve the problem of water scarcity and food insecurity.</p> Habeeb A. Yusuf Olawale J. Abidakun Samuel B. Makinde ##submission.copyrightStatement## 2020-09-24 2020-09-24 16 35 10.9734/jerr/2020/v17i117179 Design, Construction, and Testing of Maximum Power Point Tracking (MPPT) Charge Controller for Photovoltaic (PV) Power Generation <p>Maximum Power Point Tracking (MPPT) charge controller is designed for using an easy and effective way to charge a 12v battery and a laptop charger of 19v simultaneously through the principle of the bulk-boost converter. This research work is suitable for 150W solar panels, as the Maximum Power Point (MPP) of Photovoltaic (PV) power generation systems changes with variation in atmospheric conduction, an important consideration in the research work is the efficience of PV systems to track the Maximum Power Point (MPP) correctly. It enhances battery life by providing higher efficiency to it. The efficiency of the research work was calculated from the power dissipated, and also calculated the point at which the battery extracts maximum power from the PV module. As the work was tested, the voltage and current were obtained which was used to plot the voltage-current and voltage-power characteristics curve. Though a lot of works have been published on this topic, but none has researched on MPPT that can charge both 12v battery and 19v laptop charger simultaneously. Hence, this work is aimed at researching on Maximum Power Point Tracker (MPPT) that will be able to perform the above mentioned features. Also, it is the objective of this work to compare the theoretical and experimental relationship between MPPT and PWM charge controller which the efficiency of the MPPT was calculated theoretically to be 97% while, experimentally we obtained it as 91.1% while for PWM the efficiency was calculated theoretically as 75% and experimentally as 70.4% which shows that MPPT charge controller is approximately 30% efficient more than the PWM charge controller.</p> B. I. Madububa JP. C. Mbagwu D. O. Isiohia ##submission.copyrightStatement## 2020-09-25 2020-09-25 36 47 10.9734/jerr/2020/v17i117180