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Farmland Fertility Optimization for Designing of Interconnected Multi-machine Power System Stabilizer
No full textThis study describes the process of interconnected multi-machine power system stabilizer (PSS) optimization using a new intelligent technique called farmland fertility algorithm (FFA) to increase the stability of IEEE three machine nine bus power system and offset the low-frequency oscillations (LFOs) during a symmetrical 100 ms three-phase fault at bus 9. The FFA-PSS controller performance is compared with two familiar classical techniques, i.e. Genetic Algorithm (GA-PSS) and Particle Swarm Optimization (PSO-PSS) to confirm the capability of the proposed technique to realize improved system stability enhancement. The Eigenvalue simulation results with FFA produce stable Eigenvalues that increase the damping ratio of the Electromechanical Modes (EMs) to more than 0.1 with smaller overshoots and time to settle which shows the effectiveness of the method for multi-machine stability improvement. Also, the phasor simulation results show that the transient responses of the system rise time, settling time, peak time and peak magnitude were all impressively improved by an acceptable amount for the interconnected system with the proposed FFA-PSS thus, was able to control the LFOs effectively and produces enhanced performance compared to the GA and PSO based PSS. Similarly, the result validates the effectiveness of the proposed FFA tuned PSS for LFO control which demonstrates robustness, efficiency, and convergence speed ability than the classical GA and PSO tuning methods
Comparison of Artificial Neural Network (ANN) and Response Surface Methodology (RSM) in Predicting the Compressive Strength of POFA Concrete
No full textThis study presents a comparative study between Artificial Neural Network (ANN) and Response Surface Methodology (RSM) in predicting the compressive strength of palm oil fuel ash (POFA) concrete. The comparison was made based on the same experimental datasets. The inputs investigated in this study were percentage of POFA replacement and water-to-cement ratio. The methods employed in ANN and RSM were feedforward neural network and face-centered central composite, correspondingly. The comparison between the two models showed that RSM performed better than ANN with coefficient of determination (R2) closer to 1 with 0.9959. In addition, all the predicted results by RSM against the experimental results fell within 10% margin. For ANN model, however, three of its predicted results were outside the 10% margin. Percentage of POFA as cement replacement was also found to have greater impacts on the compressive strength of concrete than water-to-cement ratio. Lastly, the optimization of the proportions using RSM predicted that the maximum strength of POFA concrete is 32.19 MPa
No full textQuestions have been raised by many filmmakers over the years as to whether the 1965 coup in Indonesia was the handiwork of the Indonesian Communist Party. American/British documentary filmmaker, Joshua Oppenheimer, who has previously made The Act of Killing on the same subject, poses the question again with a new documentary. But this time, he takes a cinematic approach by fully utilising the language of film to create a solemn and meditative work. He focuses on the faces and the silence of the individuals involved, in an effort to probe their minds. The individuals are some of the surviving killers as well as the brother and family of one of those who were killed. Oppenheimer also places emphasis on landscape as character. In the area of the killings, the landscape stands as a silent witness to the horrors perpetrated there. The demonisation of the
communists continues till today in Indonesia, as it does in Malaysia as well as Singapore. The millennium saw revisionist histories surfacing that explored the blatant demonisation and vilification of communists. Films with a creative approach began to be made by young people who explored what had transpired, in an effort to foreground the truth
The Effect of Planned Behaviour Theory on Agropreneurship Intention: The Moderating Role of Gender
No full textMolecular docking study of the interactions between Plasmodium falciparum lactate dehydrogenase and 4-aminoquinoline hybrids
No full textMalaria is a potentially deadly disease with many anti-malarial drugs have been rendered ineffective due to Plasmodium falciparum resistance concern. Plasmodium falciparum lactate dehydrogenase (PfLDH) enzyme is a crucial malaria parasite enzyme involved in the glycolytic pathway, thus, has been considered as a potential molecular target. Initially, molecular docking was performed using AutoDock Vina, Molegro Virtual Docker, and CDOCKER software to investigate the molecular interactions of 4-aminoquinoline antimalarial hybrids compounds with PfLDH enzyme. All ten 4-aminoquinoline hybrids derivatives docked to the PfLDH binding site. The results showed that these compounds exhibited either comparable or higher binding affinity than the reference drug chloroquine, amodiaquine, and hydroxychloroquine. Visually, some of the compounds possessed functional binding interactions, possibly due to their similar structural conformation and binding interactions of chloroquine in the binding site. Apart from that, the docking results also suggest that these compounds potentially promote additional hydrogen-bonding interactions with the residues in the binding site. Interestingly, the compounds also predicted to interact with essential PHE52, VAL26, ILE54, ILE119, and ALA98 residues, which are required to act as a competitive inhibitor for this glycolytic enzyme
Fuzzy model reference adaptive controller for position control of a DC linear actuator motor in a robotic vehicle driver
No full textThis paper presents the controller development for DC linear actuator motors that are used to control the throttle and brake pedals of a passenger car with automatic transmission. The Fuzzy Model Reference Adaptive Control (Fuzzy MRAC) system allows the vehicle to follow speed vs. time profiles of driving cycles by dynamically adjusting the position of the driver pedals in a vehicle. The designed controller was implemented to a virtual vehicle model to determine the required position of the linear pedal actuators over a standard driving cycle. The drivingcycle simulation was conducted using Matlab Simulink and the performance of the controller was analyzed based on overshoot, rise time, settling time and mean square error whereas the robustness test was carried out via set-point tracking method. The result shows 19.79 s rise time, 0.1619% overshoot, 32.65 s settling time and 0.0041 mean square error. The results have proven Fuzzy MRAC to be a viable option for use in highly dynamic systems suchas automotive standard driving cycle controllers