Simultaneous design of power stage and controller for switchingpower supplies

This paper develops a method for simultaneously designing the power stage and controller for a switching power supply. The method utilizes a numerical optimization procedure, which facilitates computer-aided design. It is found that better performance can be achieved than with a traditional two-step design process, where the power stage and controller are designed sequentially. Optimization and simulation results for a buck power converter are presented to illustrate the design process and benefits     

A novel chaotic Henry gas solubility optimization algorithm for solving real-world engineering problems

The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm (HGSO). The new algorithm is named chaotic Henry gas solubility optimization (CHGSO). The hybridization is aimed at enhancement of the convergence rate of the original Henry gas solubility optimizer for solving real-life engineering optimization problems. This hybridization provides a problem-independent optimization algorithm. The CHGSO performance is evaluated using various conventional constrained optimization problems, e.g., a welded beam problem and a cantilever beam problem. The performance of the CHGSO is investigated using both the manufacturing and diaphragm spring design problems taken from the automotive industry. The results obtained from using CHGSO for solving the various constrained test problems are compared with a number of established and newly invented metaheuristics, including an artificial bee colony algorithm, an ant colony algorithm, a cuckoo search algorithm, a salp swarm optimization algorithm, a grasshopper optimization algorithm, a mine blast algorithm, an ant lion optimizer, a gravitational search algorithm, a multi-verse optimizer, a Harris hawks optimization algorithm, and the original Henry gas solubility optimization algorithm. The results indicate that with selecting an appropriate chaotic map, the CHGSO is a robust optimization approach for obtaining the optimal variables in mechanical design and manufacturing optimization problems.

     

Optimal Machine Learning Enabled Performance Monitoring for Learning Management Systems

Learning Management System (LMS) is an application software that is used in automation, delivery, administration, tracking, and reporting of courses and programs in educational sector. The LMS which exploits machine learning (ML) has the ability of accessing user data and exploit it for improving the learning experience. The recently developed artificial intelligence (AI) and ML models helps to accomplish effective performance monitoring for LMS. Among the different processes involved in ML based LMS, feature selection and classification processes find beneficial. In this motivation, this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring (GSO-MFWELM) technique for LMS. The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS. The proposed GSO-MFWELM technique involves GSO-based feature selection technique to select the optimal features. Besides, Weighted Extreme Learning Machine (WELM) model is applied for classification process whereas the parameters involved in WELM model are optimally fine-tuned with the help of Mayfly Optimization (MFO) algorithm. The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance. The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects. The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.     

Noise exposed of the operators of combine harvesters with and without a cab

A considerable number of the combine harvesters in Turkey are rather old and used without cabs resulting in unhealthy working conditions for their operators. Noise is one of the detrimental factors. This study deals with determining and comparing the noise exposed on the operators of the combines with and without a cab used for wheat harvesting in Turkey. The sound pressure levels (dB) at octave band center frequencies (31.5–8000 Hz) and the sound levels (dBA) at the ear level of the operators were measured on 37 different combine harvesters with four different makes and different years from 1976 to 2001. Fifteen of the combines were without a cab, another 15 had original cabs while remaining seven combines had cabs mounted on them after manufacturing.

The sound pressure levels were in a decreasing trend from the lower frequencies to higher frequencies. This trend was more noticeable for the combines with original cab and with the cab mounted after manufacturing compared to the ones without cab. The use of a cab was more effective in the insulation of the noise at the medium and higher frequencies, which have more bothersome effect compared to the lower frequencies. The sound pressure levels were 75–102 dB and 46–89 dB at low (31.5–500 Hz) and high (500–8000 Hz) frequencies for all combines, respectively. The sound pressure levels at the frequency of 4000 Hz at which the human ear is most sensitive were 6–17 dB lower for the combines with the cabs mounted after manufacturing and 9–28 dB lower for the ones with the original cabs compared to the combines without cab. The sound levels were 85–90, 81–83, and 76–81 dBA for the combines without cab, with cab mounted after manufacturing, and with original cab, respectively.

The study showed that the use of a cab was useful in the insulation of the noise, particularly at higher frequencies. In addition, it protects the operator from the factors having detrimental effects on the working efficiency such as high temperature and dusty environment. The authors strongly recommend mounting of a cab on to the combines currently being used without a cab in rental system in Turkey to provide healthy working conditions for their operators.     

High output impedance current-mode lowpass,bandpass and highpass filters using current controlled conveyors

Three new current-mode second-order filter configurations which employ one or two current controlled conveyors (CCCIIs) and three passive elements are presented. Each proposed filter can realize one of the bandpass, lowpass or highpass responses all at high impedance outputs. The proposed filters offer current-control of pole angular frequency ω_o without disturbing the parameter ω_o /Q. No component matching is required and all the passive and active sensitivities are low. PSPICE simulation results are given to confirm the theoretical analysis.     

Response Surface Modeling and Evaluation of the Influence of Deposition Parameters on the Electrolytic Cu-Sn Alloy Powders Production

In this article, the electrodeposition process of Cu-Sn alloy powders from tripolyphosphate (TPP)-based electrolytes was investigated as a function of deposition parameters. The effects of deposition parameters such as current density, electrolyte composition (Cu/Sn mole ratio), mechanical stirring speed, and temperature on the Cu content of alloy powder and cathodic current efficiency were evaluated using the response surface methodology (RSM). The empirical models developed in terms of deposition parameters were found to be statistically adequate to describe the process responses. The study revealed that as far as the copper content was concerned in the alloyed powders, all parameters selected had positive correlations. However, a high stirring speed and low current density led to a greater current efficiency. The morphology and chemical composition of the electrodeposited Cu-Sn alloy powders were investigated using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and inductively coupled plasma (ICP) analysis. An SEM analysis showed that the powder morphology was affected considerably by the cathodic current density and stirring speed.     

Anaerobic digestion of Aegean olive mill effluents with and without pretreatment

BACKGROUND: Olive oil production is an important economical activity in the Aegean region of Turkey. However, the effluents of the olive oil producing mills with their high organic loads and toxic compounds are causing serious environmental problems. The anaerobic biological treatment of olive mill wastewater (OMWW) using the treatment plants of the regional industries could be a method of choice and within the scope of this study floccular and granular sludges were investigated in batch mode for their success in the treatment of OMWW while producing biogas. The major limitation of this treatment is the inhibition of methanogenic bacteria by the phenolic compounds in OMWW. Thus an integrated solution was suggested in which a pre‐treatment step (dephenolization) was also introduced before biological step. RESULTS: The effluents of 27 olive mills out of 47 were found to have total phenolics (TP) less than 3 g L^?1 and could be treated anaerobically after simple dilution. The biogas production for the untreated OMWW was higher for floccular sludge than for the granular sludge (68.5 mL and 45.7 mL respectively). Combined pre‐treatment experiments, first coagulation with polyaluminum chloride, followed by flocculation with cationic polyelectrolyte and finally Fenton's oxidation, could remove 80% of TP and 95% of the total suspended solids. CONCLUSION: OMWW having TP values less than 3 g L^?1 can be treated anaerobically using floccular sludge after simple dilution and biogas can be produced. For OMWW samples having higher TP values pre‐treatment is necessary and the pre‐treatment given in this study may be used effectively. Copyright © 2010 Society of Chemical Industry