Full car passive and active damping system mathematical model was developed. Computer simulation using MATLAB was performed and analyzed. Two different road profile were used to check the performance of the passive and active damping using Linear Quadratic Regulator controller (LQR)Road profile 1 has three bumps with amplitude of 0.05m, 0.025 m and 0.05 m. Road profile 2 has a bump with amplitude of 0.05 m and a hole of -0.025 m. For all the road profiles, there were 100% amplitude reduction in Wheel displacement, Wheel deflection, Suspension travel and body displacement, and 97.5% amplitude reduction in body acceleration for active damping with LQR controller as compared to the road profile and 54.0% amplitude reduction in body acceleration as compared to the passive damping system. For the two road profiles, the settling time for all the observed parameters was less than two (2) seconds. The present work gave faster settling time for mass displacement, body acceleration and wheel displacement.

In recent years, the addition of nano and micro size filler material for fabricating composite materials are emerging concepts through which mechanical properties of the composite can be enhanced. Filler based hybrid polymer composite materials are substituting metallic materials because of their low specific wear rate, high specific strength modulus, and less water absorption. In current work, nano and micro Al2O3 filler based Glass-Jute hybrid composite have been fabricated to study the mechanical properties like hardness, impact test, specific wear rate, and flexural strength for each type of composite sample. Water absorption analysis is also carried under three different fluid media namely normal water, river water and de-ionized water-based Al2O3 nanofluid. Nano filler enriched composite attributed the higher magnitudes of hardness, impact strength, flexural strength and lower value of specific wear rate and water absorption compared to micro and normal composites. However, a nanofiller based composite is more suitable for automotive, aerospace and ship manufacturing industries.

Enrollment in courses is a key performance indicator in educational systems for maintaining academic and financial viability. Today, a lot of factors, comprising demographic and individual features like age, gender, academic background, financial capabilities, and academic degree of choice, contribute to the attrition rates of students at various higher education institutions. In this study, we developed prediction models for students' attrition rate in pursuing a computer science degree as well as those who have a high chance of dropping out before graduation using machine learning methodologies. This approach can assist higher education institutions in creating effective interventions to lower attrition rates and raise the likelihood that students will succeed academically. Student data from 2015 to 2022 were collected from the Federal University Lokoja (FUL), Nigeria. The data was preprocessed using existing WEKA machine learning libraries where our data was converted into attribute-related file form (ARFF). Further, the resampling techniques were used to partition the data into the training set and testing set, and correlation-based feature selection was extracted and used to develop the students' attrition model to identify the students' risk of attrition. Random Forest and decision tree machine learning algorithms were used to predict students' attrition. The results showed that Random Forest has 79.45% accuracy while the accuracy of Random tree stood at 78.09%. This is an improvement over previous results, where an accuracy of 66.14%. and 57.48% were recorded for random forest and Random tree respectively. This improvement was because of the techniques demonstrated in this study. It is recommended that applying techniques to the classification model will improve the performance of the model.

Interaction between parametric excitation and self-excited vibration has been subjected to numerous investigations in continuous systems. The ability of parametric excitation to quench self-excited vibrations in such systems has also been well documented. But such effects in discontinuous systems do not seem to have received comparable attention. In this article, we investigate the interaction between parametric excitation and self-excited vibration in a four degree of freedom discontinuous mechanical system. Unlike majority of studies in which oscillatory nature of stiffness accounts for parametric excitation, we consider a much more practical case in which parametric excitation is provided by a massless rotor of rectangular cross section with a cylinder-like mass concentrated at the center. The rotor arrangement is placed on a friction-induced self-excited support in the form of a frame placed on a belt moving with constant velocity. This frame is connected to a supplementary mass. A Stribeck friction model is considered for the mass in contact with the belt. The frictional force between the mass and the belt is oscillatory in nature because of the variation of normal force due to parametric excitation from the rotor. Our investigations reveal mutual synchronization of parametric excitation and self-excited vibration in the system for specific parameter values. The existence of a stable limit cycle with constant synchronized fundamental frequency, for a range of parametric excitation frequencies, is established numerically. Investigation based on frequency spectra and Lissajous curves reveals complex synchronization patterns owing to the presence of higher harmonics. The system is also shown to exhibit Neimark–Sacker bifurcations under the variation of belt velocity. Furthermore, variation in belt velocity and coupling stiffness is seen to cause a breakup of quasi-periodic torus with small-amplitude oscillations to form large amplitude chaotic orbits. This points toward the possibility of vibration suppression in the system by tuning the parameters for stabilizing the small-amplitude quasi-periodic response. An example of co-existence of different attractors in the system is also presented.

This work is aimed at applying holonic control system to poultry house travelling hopper feeders with the comparative cost analysis. It adopts HCBA which is suitable for controlling the reconfigurable automated processes. The feeder consists of parts for different types of poultry feeds dispensable from the feed reservoirs and carried around by travelling hoppers along the feed carts. The simulations were carried out using MATLAB and SIMATIC software. The responses of the speed of each traveling hopper were determined to be 1.04 sec, 1.91 sec and 0.0841% for rise time, settling time and percentage overshoot respectively. The parameters of the embedded controller in STEP 7 CONT_C FB41 data block translate to a constant gain of 10, integral time constant of 100 ms and derivative time constant of 280 ms. Visual results from the HMI show the system’s ability for customization, cooperation and autonomy for implementation of any poultry feeding program. The cost analysis shows that it is profitable for farm capacity of 10,000 birds and above with low labour cost and average annual energy cost of about N708,000. The feed wastage loss is reduced by 66% while depreciation is 10% as compared to cage system with belted conveyor feeder.