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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Fatimah Sham Ismail
Universiti Teknologi Malaysia
Computer Science & IT Engineering

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Optimization of artificial neural network topology for membrane bioreactor filtration using response surface methodology Syahira Ibrahim; Norhaliza Abdul Wahab; Fatimah Sham Ismail; Yahaya Md Sam
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (925.565 KB) | DOI: 10.11591/ijai.v9.i1.pp117-125

Abstract

The optimization of artificial neural networks (ANN) topology for predicting permeate flux of palm oil mill effluent (POME) in membrane bioreactor (MBR) filtration has been investigated using response surface methodology (RSM). A radial basis function neural network (RBFNN) model, trained by gradient descent with momentum (GDM) algorithms was developed to correlate output (permeate flux) to the four exogenous input variables (airflow rate, transmembrane pressure, permeate pump and aeration pump). A second-order polynomial model was developed from training results for natural log mean square error of 50 developed ANNs to generate 3D response surfaces. The optimum ANN topology had minimum ln MSE when the number of hidden neurons, spread, momentum coefficient, learning rate and number of epochs were 16, 1.4, 0.28, 0.3 and 1852, respectively. The MSE and regression coeffcient of the ANN model were determined as 0.0022 and 0.9906 for training, 0.0052 and 0.9839 for testing and 0.0217 and 0.9707 for validation data sets. These results confirmed that combining RSM and ANN was precise for predicting permeates flux of POME on MBR system. This development may have significant potential to improve model accuracy and reduce computational time.
Thermal Performance Analysis for Optimal Passive Cooling Heat Sink Design Nur Warissyahidah Badrul Hisham; Fatimah Sham Ismail; Muhammad Azmi Ahmed Nawawi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 2: June 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i2.6140

Abstract

Recent advances in semiconductor technology show the improvement of fabrication on electronics appliances in terms of performance, power density and even the size. This great achievement however led to some major problems on thermal and heat distribution of the electronic devices. This thermal problem could reduce the efficiency and reliability of the electronic devices. In order to minimize this thermal problem, an optimal cooling techniques need to be applied during the operation. There are various cooling techniques have been used and one of them is passive pin fin heat sink approach. This paper focuses on inline pin fin heat sink, which use copper material with different shapes of pin fin and a constant 5.5W heat sources. The simulation model has been formulated using COMSOL Multiphysics software to stimulate the pin fin design, study the thermal distribution and the maximum heat profile.
Electronics system thermal management optimization using finite element and Nelder-Mead method Nurul Kausar Ab Majid; Fatimah Sham Ismail
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i5.12796

Abstract

The demand for high-performance, smaller-sized, and multi-functional electronics component poses a great challenge to the thermal management issues in a printed circuit board (PCB) design. Moreover, this thermal problem can affect the lifespan, performance, and the reliability of the electronic system.  This project presents the simulation of an optimal thermal distribution for various samples of electronics components arrangement on PCB. The objectives are to find the optimum components arrangement with minimal heat dissipation and cover small PCB area. Nelder-Mead Optimization (NMO) with Finite Element method has been used to solve these multi-objective problems. The results show that with the proper arrangement of electronics components, the area of PCB has been reduced by 26% while the temperature of components is able to reduce up to 40%. Therefore, this study significantly benefits for the case of thermal management and performance improvement onto the electronic product and system.
Comprehensive Pineapple Segmentation Techniques with Intelligent Convolutional Neural Network Muhammad Azmi Ahmed Nawawi; Fatimah Sham Ismail; Hazlina Selamat
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 3: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i3.pp1098-1105

Abstract

This paper proposes an intelligent segmentation technique for pineapple fruit using Convolutional Neural Network (CNN). Cascade Object Detector (COD) method is used to detect the position of the pineapple from the captured image by returning the bounding box around the detecting pineapple. Image background such as ground, sky and other unwanted objects have been removed using Hue value, Adaptive Red and Blue Chromatic Map (ARB) and Normalized Difference Index (NDI) methods. However, the ARB and NDI methods are still producing misclassified error and the edge is not really smooth. In this case Template Matching Method (TMM) has been implemented for image enhancement process. Finally, an intelligent CNN is developed as a decision maker to select the best segmentation image ouput from ARB and NDI. The results obtained show that the proposed intelligent method has successfully verified the fruit from the background with high accuracy as compared to the conventional method.
Co-Authors Hazlina Selamat Muhammad Azmi Ahmed Nawawi Norhaliza Abdul Wahab Nur Warissyahidah Badrul Hisham Nurul Kausar Ab Majid Syahira Ibrahim Yahaya Md Sam