Agus Saptoro

A Modified Kennard-Stone Algorithm for Optimal Division of Data for Developing Artificial Neural Network Models

Abstract This paper proposes a method, namely MDKS (Kennard-Stone algorithm based on Mahalanobis distance), to divide the data into training and testing subsets for developing artificial neural network (ANN) models. This method is a modified version of the Kennard-Stone (KS) algorithm. With this method, better data splitting, in terms of data representation and enhanced performance of developed ANN models, can be achieved. Compared with standard KS algorithm and another improved KS algorithm (data division based on joint x - y distances (SPXY) method), the proposed method has also shown a better performance. Therefore, the proposed technique can be used as an advantageous alternative to other existing methods of data splitting for developing ANN models. Care should be taken when dealing with large amount of dataset since they may increase the computational load for MDKS due to its variance-covariance matrix calculations.

Oxygen transfer to cassava starch solutions in an aerated, well-mixed bioreactor: Experimental and mass transfer studies

Experimental and mass transfer studies of oxygen transfer to cassava starch solution in an aerated, well-mixed bioreactor of 2 L have been carried out. The volumetric mass transfer coefficient was estimated and parametric studies were performed to study the effect of process variables of stirring rate, aeration rate, concentration of starch and temperature on the volumetric mass transfer coefficient. From the experimental results, it is evident that the first two and the last variables are directly proportional to the volumetric mass transfer coefficient. However, the volumetric mass transfer coefficient is inversely proportional to the concentration of the starch. Also, the saturation dissolved oxygen concentration is greatly affected by temperature and starch solution concentration. Whereas, stirring and aeration rates have neutral impacts on saturation dissolved oxygen concentration. Simulated data generated from obtained volumetric mass transfer coefficient agrees well with the experimental data, which indicates the accuracy of the coefficient.

EXTENDED AND UNSCENTED KALMAN FILTERS FOR ARTIFICIAL NEURAL NETWORK MODELLING OF A NONLINEAR DYNAMICAL SYSTEM

Recently, artificial neural networks, especially feedforward neural networks, have been widely used for the identification and control of nonlinear dynamical systems. However, the determination of a suitable set of structural and learning parameter value of the feed-forward neural networks still remains a difficult task. This paper is concerned with the use of extended Kalman filter and unscented Kalman filter based feedforward neural networks training algorithms. The comparisons of the performances of both algorithms are discussed and illustrated using a simulated example. The simulation results show that in terms of mean squared errors, unscented Kalman filter algorithm is superior to the extended Kalman filter and back-propagation algorithms since there are improvements between 2.45–21.48% (for training) and 8.35–29.15% (for testing). This indicates that unscented Kalman filter based feedforward neural networks learning could be a good alternative in artificial neural network models based applications for nonlinear dynamical systems.

Reviews on drag reducing polymers

Polymers are effective drag reducers owing to their ability to suppress the formation of turbulent eddies at low concentrations. Existing drag reduction methods can be generally classified into additive and non-additive techniques. The polymer additive based method is categorized under additive techniques. Other drag reducing additives are fibers and surfactants. Non-additive techniques are associated with the applications of different types of surfaces: riblets, dimples, oscillating walls, compliant surfaces and microbubbles. This review focuses on experimental and computational fluid dynamics (CFD) modeling studies on polymer-induced drag reduction in turbulent regimes. Other drag reduction methods are briefly addressed and compared to polymer-induced drag reduction. This paper also reports on the effects of polymer additives on the heat transfer performances in laminar regime. Knowledge gaps and potential research areas are identified. It is envisaged that polymer additives may be a promising solution in addressing the current limitations of nanofluid heat transfer applications.

Mass Transfer Coefficients and Correlation of Supercritical Carbon Dioxide Extraction of Sarawak Black Pepper

Abstract Bioactive compound, namely piperine, was extracted from Sarawak black pepper using supercritical carbon dioxide extraction. Experiments were carried outin the range of 3,000–5,000 psi (20.7–34.4 MPa) pressures, 318–328 K temperatures, 0.4–1 mm mean particle sizes and5–10 ml/min carbon dioxide flow rates. Experimental data analysis shows that extraction yield ismainly influenced by pressure, particle size and coupled-interactions between these two variables. Extraction process was modeled accounting for intraparticle diffusion and external mass transfer. The kinetics parameters for the internal and external mass transfers were evaluated and estimated. Mass transfer correlation was also developed. From simulation results, good agreement between experimental and simulated data has been found.

Surface tension profiles of nanofluid containing surfactant during microwave irradiation

Manipulation of the surface tension is useful in improving heat and mass transfer performances of nanofluids in thermal systems. In our previous study, the effect of microwave irradiation on the reduction of surface tension of nanofluids (Fe2O3) was found even after it was turned off. In this study, a synergistic effect of microwave irradiation and surfactant addition (SDS) was investigated to obtain further surface tension reduction of nanofluid. Experimental results indicate that surfactant addition is effective for wider particle number density in reducing surface tension, and the reduction level strongly depends on the surfactant concentration. On the other hand, effect of the number density on the surface tension reduction is less significant for the same concentration of surfactant. From the obtained data, a combination of microwave irradiation and surfactant addition shows potential to be used as a promising method to manipulate surface tension of nanofluids.

Isolation of Thermophilic Lignin Degrading Bacteria from Oil-Palm Empty Fruit Bunch (EFB) Compost

Empty Fruit Bunch (EFB) is a potential and sustainable feedstock for bioethanol production due to its high cellulosic content and availability in Malaysia. Due to high lignin content of EFB and the lack of effective delignification process, commercial bioethanol production from EFB is presently not viable. Enzymatic delignification has been identified as one of the key steps in utilising EFB as a feedstock for bioethanol conversion. To date, limited work has been reported on the isolation of lignin degrading bacteria. Hence, there is a growing interest to search for new lignin degrading bacteria with greater tolerance to temperature and high level of ligninolytic enzymes for more effective lignin degradation. This study aimed to isolate and screen thermophilic ligninolytic microorganisms from EFB compost. Ten isolates were successfully isolated from EFB compost. Although they are not capable of decolorizing Methylene Blue (MB) dye under agar plate assay method, they are able to utilize lignin mimicked compound – guaiacol as a sole carbon on the agar plate assay. This infers that there is no correlation of ligninolytic enzymes with dye decolourization for all the isolates that have been isolated. However, they are able to produce ligninolytic enzymes (Lignin peroxidase, Manganese peroxidase, Laccase) in Minimal Salt Medium with Kraft Lignin (MSM-KL) with Lignin Peroxidase (LiP) as the predominant enzyme followed by Manganese Peroxidase (MnP) and Laccase (Lac). Among all the tested isolates, CLMT 29 has the highest LiP production up to 8.7673 U/mL following 24 h of growth.

Computational Fluid Dynamics-Based Hydrodynamics Studies in Packed Bed Columns: Current Status and Future Directions

Abstract A careful review of the literature reveals that extensive research has been done on the hydrodynamics in packed bed columns using turbulence models. It can be noted that the choice of turbulence model is influenced by the number of phases, type of fluid, Reynolds number range and the type of packing. Thus, comparison of turbulence models for the selection of a suitable model assumes great importance for the better prediction of flow pattern. This is due to the fact that poor prediction of the flow pattern can lead to a limited heat and mass transfer model as the rate of transfer processes in packed bed is governed by the hydrodynamics of the packed bed. The aim of this paper is to give a review of the computational fluid dynamics (CFD)-based hydrodynamics studies of packed bed columns with the primary interest of studying pressure drop and drag coefficient in packed beds. From the literature survey in Science Direct database, more than 48,000 papers related to packed bed columns have been published with more than 3,000 papers focused on the hydrodynamic studies of the bed to date. Unfortunately, there are only a few studies reported on the hydrodynamics of packed columns under supercritical fluid condition. Therefore, it is imperative that the future work has to focus on the hydrodynamics of supercritical packed column and particularly on the selection of suitable turbulence model.

Septage treatment using vertical-flow engineered wetland: A critical review

Septage, which is a mixture of sludge, scum and liquid, is a type of faecal sludge that is specifically removed from an individual septic tank. Their biochemical stability and high concentration of solids and nutrients are the major technical challenges towards effective treatments in the existing wastewater treatment systems. A subsurface vertical-flow engineered wetland (VFEW) is, therefore, introduced as a feasible decentralized septage treatment option for small or medium communities due to its abilities in achieving excellent treatment and energy efficiency and reasonable cost through a simple operation. In general, the VFEW removes suspended solids, organic matter and nitrogenous components constituted in raw septage efficiently and sustainably. This paper presents a critical review on the state-of-the art of septage treatment using vertical-flow engineered wetland with regards to their characteristics and operation. The system-factor such as substrate profile and operational factors such as solid loading rate (SLR) and frequency of loading have been generally agreed as major factors governing the effectiveness of VFEWs. The selection of substrates is crucial to ensure a long-term usability of the VFEW with regards to the clogging phenomenon. The SLR, which ranged from 30 to 250 kg TS m -2 y -1 , is of great importance to the treatment capability. The frequency of loading determines the rate of oxygen renewal, microbial growth and mineralization of the accumulated sludge deposit within the VFEW system. Future research directions and recommendations are also outlined.

Promotion of nucleation for nano-particle formation by two-stage microwave irradiation

Microwave has been widely used for nano-particle synthesis because rapid growth and mono-dispersed particle size can be obtained. In our previous work, it was found that bubble formation during the irradiation is greatly affected by particle size and suspension density. Nevertheless, the underlying mechanism has not been clearly understood, especially pertinent to superheat behavior caused by the higher power when colloidal particle of ferric hydroxide was produced by heating ferric chloride solution under the irradiation. In this study, to prevent superheat behavior, two-stage irradiation was proposed in nano-particle formation process. Based on in-situ measurement data, such as the profiles of bubble size, final particle size and brightness of scattering light of suspension, it is evident that nucleation of nano-particle is promoted by higher power of the first irradiation. As a result, particle number density became higher, and then microwave absorbance energy was evenly distributed to each particle. Due to suppression of heat generation in a particle, bubble size became smaller. Two-stage irradiation became more advantageous in obtaining smaller particle than continuous irradiation because lower power of the second irradiation prevents superheat behavior.