Air pollution is responsible for an estimated 5.5 million deaths in 2013 which costed the global economy approximately US$225 billion in lost labor income. To address the problems caused by air pollution, this study aims to develop a low-cost and portable air quality monitoring system that detects the levels of CO, PM2.5, PM10, temperature, and humidity. Using Internet of Things (IoT), the data that the system gathers can be accessed through the internet. Moreover, the system assesses the obtained data through a comparative analysis with the AQI. The Iterative Design Loop method was used in the development of the air quality monitoring system. Furthermore, the sensors were programmed using the Arduino Integrated Development Environment (IDE). Using the Welch’s t-test, it was found that the obtained data of the system is not significantly different to that of the standard air quality monitoring systems. To achieve more accurate data from the developed system, the raw data of the developed and standard system were calibrated through an equation from the trendline. Through the use of Acer CloudProfessor, the study successfully developed an air quality monitoring system that can be accessed through the internet.

This research work focuses on the design and development of Class 2B-lpl compliant constant-force compression slider mechanism. It also expresses the desire to simplify the behavioral model for easy usage. Results obtained indicated an average non-dimesionalized parameter value of 1.2573, 1.2991, 1.3483, and 1.4081 for a 10, 20, 30, and 40% displacement respectively. The result also shows that the average force generated by the mechanism for a 10, 20, 30, and 40% displacement were 901.23N, 316.56N, 171.17N, and 110.44N respectively using the maximum flexible segments parameter values for the different percentages of mechanism slider displacement. This indicates clearly that using the non-dimensionalized parameter, the average force generated by this class of mechanism can easily be determined which greatly simplifies its usage.

In this paper, modeling and simulation of large hydropower plant in real-time platform named Real-Time Laboratory (RT-LAB) is carried out. First, a hydropower plant model consisting of nonlinear hydro turbine with PID governor and synchronous generator (SG) with DC1A excitation system and connected to grid is developed in MATLAB/Simulink environment. This model is then simulated in RT-LAB after the modification of MATLAB/Simulink model required for suitable operation in RT-LAB environment. Finally, the real-time simulation of hydropower plant when subjected to disturbances of load addition, reduction of load and short circuit fault analysis is presented and discussed.

In this paper, we propose a suitable textural feature for diagnosis of dental caries in digital radiographs. The dental diagnosis system consists of Laplacian filter for image sharpening, adaptive threshold and morphological operations for segmentation, and support vector machine (SVM) as a classifier. In segmented image, textural features are extracted, and applied to the classifier, to classify the image as caries or normal. Experimental results indicate that GLCM (Grey Level Co-occurrence Matrix) and GLDM (Grey Level Difference Method) textural features are giving better performance measures as compared to other types of textural features with an accuracy of 96.88%, sensitivity of 1, specificity of 0.8667 and precision of 96.08%. The data were analyzed by Analysis of Variance (ANOVA), at a significant level of 5%. This result indicates that the interaction of feature extraction methods on performance measures are significant. Hence, GLCM or GLDM features provide reliable decision support for dental caries diagnosis.

This work focuses on the design and development of a mixed-mode domestic solar dryer in which the slices of pepper, okra and yam were dried simultaneously by both direct radiation through the transparent glass roof of the drying chamber and by the heated air from the solar collector. The dryer was made up of the solar collector, the desiccant chamber and the drying chamber which contains a rack of three trays. The air comes in through the air inlet and heated up within the solar collector and then channeled through the drying chamber by natural convection where it is utilized for drying purposes. The development was done using locally sourced and readily available materials such as wood, transparent glass sheet, mild steel metal sheet, mosquito galvanized wire mesh and chicken galvanized wire mesh. The maximum temperature attained by the solar collector, drying chamber during test were 69oC and 55oC respectively, with a corresponding ambient temperature of 39oC. The mass of water removal of 43g, 136g and 255g from pepper, okra and yam slices respectively was achieved making use of the passive solar food dryer as against the water removal of 39g, 126g and 218g from pepper, okra and yam slices respectively achieved using the sun drying method which indicates a difference of 4g, 10g and 37g for pepper, okra and yam slices respectively. The rapid rate of drying achieved with the use of this dryer shows that it has the ability to dry food items rapidly to an acceptable moisture content level.